{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import requests\n",
    "import numpy as np\n",
    "import itertools\n",
    "import talib\n",
    "import quandl\n",
    "import tensorflow as tf\n",
    "import matplotlib.pyplot as plt\n",
    "import statsmodels.api as sm\n",
    "import seaborn as sns\n",
    "import time\n",
    "import tushare as ts\n",
    "from tensorflow.contrib.layers.python.layers.initializers import xavier_initializer\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "# select two stocks which passed co-intergration test (cheating exist)\n",
    "quandl.ApiConfig.api_key = 'CTq2aKvtCkPPgR4L_NFs'\n",
    "data=pd.DataFrame()\n",
    "for s in ['JNPR','HPQ']:\n",
    "    stock=quandl.get_table('WIKI/PRICES', date={'gte':'2002-01-01'}, ticker=s)\n",
    "    stock.index=stock['date']\n",
    "    data[s+'_p']=stock.adj_close\n",
    "    data[s+'_v']=np.log(stock.adj_volume)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7f97effa1550>"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jez537lzMmDEDAPDggw+id+/eKC4uxogRI/Dhhx+q682ZMwdDhw7F0KFDUVJSghUrVsRz\n2CGxawMRERGRhluSYRbhAwktLglOly/74HizEw63hK0Hj8V6iERElELuuOMO/P73v8e2bdswYcIE\nHDlyBB9//DFeeOEFfPXVVygoKMC6deswadIkrFq1Cr179070kBlIICIiItKSZECECyRYTGh2uuHU\nZCQ0u6QQ7yAiokQ79OijaNm2PaqfaR82FD3uuy8qnzVs2DBYLBZUVlZi1qxZmD17NgoKCgAAo0eP\nxo033ojnnnsOjz76aMB7Fy9ejJdeeglvv/02AGDFihV44oknsGjRoqiMzR8DCUREREQakiTDHGby\nZ6bN7AkkuH3BgxZNO0hZlsMGI4iIKD00NTWhuLhYfV5dXY1JkyYFrLdq1SqYTCYUFhZiy5YtOPXU\nU3Wvl5SU4OWXXzbcxgUXXIBbbrkFDQ0NyM7Oxvz58zFlypTo/iAaDCQQERERabgjrJHQ7NRPbWh2\n+oIKx5pcyM8KXqyRiIjiL1qZA62VmZmJ0tJS9fncuXOxZs0a9fmTTz6J1157Dbm5uZg/f36bAtEW\niwUXXXQRFi5ciKuuugofffQRHn/88aiM33B7MftkIiIioiQkSTJMkUxtcLnhcGunNvgyEg4fb2Yg\ngYiIIqLUSNAaPnw41q5di/POO09dtnbtWpSUlAT9nClTpuDZZ59Fly5dUFJSgtzc3JiNmV0biIiI\niDQiyUiwW82QZaDR4VKXtWgyEr7dXRWz8RERUeq7++67MXPmTFRVeY4npaWlWLBgAaZNmxb0PWef\nfTbWrVuHF198MabTGgBmJBARERHpSHLwjISV956HJocby78/CgA43uwLJGgzEh74YAt+Ma4opuMk\nIqLUNWnSJFRUVGD8+PFwuVw4dOgQNmzYgMLCwqDvMZvNuOyyyzB37lzMmzcvpuNjRgIRERGRhiQh\naCChZ34mBhTm4MixZgDA1gpfq0dtsUUiIiJFfX297vnUqVPx7LPPAgAefPDBgGkNiunTp2P79u3Y\nvn07Jk+ejAceeACyLBuuq3j22WdRX1+PrKys6Aw+CGYkEBERUdp767v9OH1AV5zQNQvuCLo2dMm2\nAQA2lNeqy7TFFomIiKLFYrHg1VdfTfQwdJiRQERERGnN5ZZw97sbcfk/vwYQWY2Ec4d2AwA0OXxZ\nCHVNztgNkoiIyGvy5MkoLi7W/bdkyZK4joEZCURERJTWml2eTILqBgeAyLo22C2eezFr9taoy5T3\nKxwuCTYL79kQESWaLMttaqnYUS1YsKBd7w83PSISPLoRERFRWvOvbRBR1waLOWBZdYND9z5tRwci\nIkqMjIwMVFVVReXiORXIsoyqqipkZGS063OYkUBERERpbd2+Wt3zFqekZhwE4/969zw7Kutb4JZk\n9O6UiQO1TWhwuNEptrWuiIgojD59+qC8vBxHjx5N9FA6jIyMDPTp06ddn8FAAhEREaWtXUeO45ev\nrFGfy7KMFpfbMONAq7O32KKib+csHKzzdHLokm3zBBJamJFARJRoVqsV/fv3T/QwUg6nNhAREVHa\nWrLlsO650y1DkoEMa/hTpKE9cgEAi247E11zbKiobQIAdMqyAgADCURElLKYkUBERERpp9npNuyy\ncOS4J6sgXEYCALR4izRm2szokm3HkeMtAHytIRsd7qDvJSIiSmbMSCAiIqK0c8N/VmPso8sgSfri\nW1X1ns4L9ggyEpTCinaLCQU5vqkOnbM8j5mRQEREqYoZCUREFBGl2nEqtU+i9LVqTzUAwL+Gd4O3\n00K4YosA8OIvSvD++gPo3SkTXbMNAgns2kBERCmKGQlERBSRu97ZiKtfWJnoYRBFlX83sMYWz3SE\nSKY29C/Ixh0XDoEQAl1y7Ory3AzPfRqnm63GiIgoNTEjgYiIIvLO2vJED4Eo6mx+mQetyUjQKtBk\nJGTZPEEIt8RAAhERpSZmJBAREVHacngLJv7jZ8UAfAUSI6mRoNVFUyMh0xtIcDGQQEREKYqBBCIi\nIkpbmw7UAfBlERzzdnLIsIaf2qCVl2FVH2fbPAmf/oUciYiIUgUDCUREZEiSZLXAotbOw8exbNvh\nBIyIKPo+8/4tK1Mc/vrJdgBAfqY16HuM9MzPUB8P65UHgBkJRESUusIGEoQQGUKI1UKIDUKILUKI\nh7zL5woh9gghSr3/Fcd+uEREFC8D7vsYt76xDgBQUdukLr/wyS9w87w1iRoWUUxYzfpTIm2GQSSE\nEPjlhP748aheahDiz4u2Rm18REREHUkkxRZbAJwny3K9EMIK4CshxCfe1+6SZfmd2A2PiIgS6eNN\nhwAAn245lOCREMXOgMJsmE36tqZ5rcxIAID7Lx0OAGh2utVlNQ0OdNYUYiQiIkoFYTMSZI9671Or\n9z/m6hERpRFbBK3wiJKFLMvIsJrUzIEnry6GxS+QkGtve2MrbVBi19H6EGsSERElp4hqJAghzEKI\nUgBHACyVZXmV96W/CCE2CiGeFELYg7z3FiHEGiHEmqNHj0Zp2EREFE8tLnf4lYiSxIbyOjQ7Jcw4\ndxDKHrsUo/p2ghD6QILJL7DQGmbNZ+06wkACERGlnogCCbIsu2VZLgbQB8AYIcQIAPcCGArgNABd\nAMwM8t45siyXyLJcUlhYGKVhExFRvKzaXYWHFnKuN6WOy5/7GgBgMfsu+NsRNwigDUL8wEACERGl\noFZ1bZBluRbAcgAXybJ80DvtoQXAywDGxGKAREQUf9q2dX/7dEcCR0IUO9qCiv41EqKlvsUVk88l\nIiJKpEi6NhQKITp5H2cCuBDAdiFET+8yAeByAJtjOVAiIoofpySpj1eXVSdwJETRd82YvgCAS0/u\nqS4ziegGErY+PBEFOXYYdFAlIiJKepFUEuoJYJ4QwgxP4OEtWZYXCSE+F0IUAhAASgFMj+E4iYgo\njtwSr34odeXYLciymZFh9RURjXYgIctmgcUkILM+NRERpaCwgQRZljcCOMVg+XkxGRERESWc0218\n8fPSDSW4ed6aOI+GKLpe/HJPwDKTJkfzroknRmU7JgFmJBARUUpqVY0EIiJKD8EyEixm32Fjwfry\neA2HKGpqGx2Gy7UZCSf1yovKtoQQYHIPERGlIgYSiIgogMstGS63aArS3TF/A7YfOhavIRFFxdaD\nxn+z2kBCNKc5cGoDERGlIgYSiIgogDPIbVT/CyxLjCrdE0XL66v24tnPd6rPdxw6brie9k85WoEE\nIQDGEYiIKBVFUmyRiIjSjNugRsIZA7vCJRlnKhB1VPcv8DSVmnHeYADAwbpmAIDVrA8W6DMSorNt\nkxCMIxARUUpiRgIREQVwGgQM3vjl6RDQX2EFmQFB1GG1uCSYBLD+gR/plps10QMRxYwEidUWiYgo\nBTGQQEREAYIVWxw/qCtOOaGT+pwZCpRsnG4JXbJtyLHrkzKFbmpDdLYlwK4NRESUmhhIICKiAM4g\nqQZCCJwxsKv6/LVv98ZrSERR4XLLsJgCT3+0GQmmKEUSBKc2EBFRimIggYiIArgMaiQotNMb3ly9\nHy0udzyGRBQVTkmCxRwYKIhFjQQhAJkpCURElIIYSCAiogChpiz4X2Q1Ozi9gZKH0y3DZg48/dFO\nbYhajQRwagMREaUmBhKIiCjA3qpG9fH4QV3x7b3n+170u8hy80qJkoBbklFW2YCVP1QaZiSYdRkJ\n0ZzawO8HERGlHrZ/JCKiAHe+tQEAMPmU3rj/0mEoyLGrr/lnJAQrzEjUkThcEs55YgUAoFtuRsDr\nWTbfKVGUZjYwI4GIiFIWAwlERBTUY1eOhN1i1i3zbwHJ9naUDPZWN6iPrQYZCZk23995tLJsTEIw\nkEBERCmJUxuIiCgo/yACEDCzAS6DjISXv96D/vd+BInZCtRBXPSPL9XHVoMaCQCw8y8X44XrT8Up\nfTsZvt5aQjDQRkREqYmBBCIiahX/e7lGwYK/f7oDsgzsr2kMeI0o0YxqJACeAMPEk3pErdgiAFZI\nICKilMRAAhFRmpNlGXsqGwKWj+qTb7i+Ejfo3SkTgHGNhD5dsgAAZ89eEZ1BErVBeZBAVrCMhGgT\nnNpAREQpioEEIqI098bqfTj3iRX4rqwagC8wcN7Q7obrK60hM6wm7/PAK6V+3kACUSKdOWu54fJo\nZhyE4ilMykgCERGlHgYSiIjSXOm+WgDA7qP1AIAWlxsAYLcaHyKcbs+FUYbVUz/BaA54Toanlu/A\nwuzoDpYoCvZWBWbgxIKnRkJcNkVERBRXDCQQEaU5k/furBIPaHZ6Mw4swQIJntft3teNpjY4XMo6\ngcUaiRJtb1V8ancICMic20BERCmIgQQiojSnZHlLaiBByUgwDgK43PoggVEgQfkM5f9EidArPwMn\nds8NWP67C4fEZftCcGIDERGlJgYSiIjSnBJIkL2XPMrFf0aQqQ0KpfK9USChvsUFANhd2YDjzc5o\nDZWoVVpcEvIyLbpld008EbedPzgu22exRSIiSlUMJBARpTml8JwSDzje7AkC5GVYDddXrovMJm8g\nweBKSQkkAMCR4y1RGilR67S4pIC/41+dPTBu2xcwriFCRESU7CzhVyEiolSm1q/3XvDUNnkyCDpl\nBQkkeK+LLCZPLFoKMbUBABo0QQWieHK6JeRm+E51LCYBkyk+HRsAoKK2CXVNzMghIqLUw0ACEVGa\n86+RUNvoAADkZ9pCrq8UWzRq/6id7lDbyAspSgynW0K2PXGnOszGISKiVMVAAhFRmnvt230AlJ73\nUO+gBstIuOOCIWhxSrhoZA98tOlgQEbC9FfX4oejvvZ6Nd7ABFE8uSUZkuxrRQoAFwzrnsARERER\npQ7WSCAiIgCA2TtVQckgyM80DiR0zrZh1lUnI8d7p9e/RsLiLYcAABMGF+g+jyielDalOTZfIOGp\na4oTNRwiIqKUwkACEVGaG9YzDwCwuaIOgOfCP9dugdUc+hChFls0mNoAAF2yPVMjmJFAiaBMucnQ\ntDFVWpYSERFR+zCQQESU5qzeNo5vrPJMcahtciA/yLQGLbMIHUiwmU3IsJrQ6HAbvk4US06XJyNB\naVOq/J0TERFR+7FGAhFRmvMPBNQ2OoPWR9AKl5FgNgnYLWa0OBlIoPhzSp5AgtVswks3lGBQt5wE\nj4iIiCh1MCOBiCjNaQMBeyob8Pn2I2r9g1CUQIIkGwcSTCaBDKsJLd47w0Tx5HR7/i6tZoHzh3VH\nv67ZcR9Dr/wMw+UVtU1xHgkRxcKohz7F9S+tSvQwiBKCgQQiojSnDQTc+PJqAIAjgot/JZCgbf8o\ny/rHdouZgQRKCJfbl5GQKD877QQA0HU2Wbu3Gmc89jneWVueqGERUZTUNTnx5c7KRA+DKCEYSCAi\nSnPajISyqkYAQNcce9j3mQxqJGgftzgl2C0mNHNqA8VBTYMD2w4eU587O0AgQdn0V7t8Fxo7DtcD\nANaUVSdiSERERFHBQAIRURrbfugYfjjaELA8yxa+ur3R1AZtdkKLS4KdUxsoTiY99xUufupL9bl2\nakOiKC1Vf/Gf1b5lYYqUEhERJQMWWyQiSmPLtx81XJ5pDR9IsChTG9zBAglubD5wDMAx/7cSRd3+\nal/dgWanG1PmfAugY2QkaJmUIqVBaosQUXJoaHEleghECcWMBCIiCpARQSDBZJCR4HbrMxIUMi+a\nKI7+9un3qGtyAgAsCQ0kBG5bGQ6/EkTJ7aQ/LVEff3/oeAJHkjrW76vBqt1VqGeQJikwI4GIKI3J\nML6aufnM/mHf60vR9i1zSb4n2kCCJAMJzDCnNPO/Hb5Mm0RObcg2mCJkVFuEiJJLTYND95wXvtEx\n+Z/fqI93P3qJesOCOiZmJBARkc7dF52Ivl2ywq5nNkjR1k5t0MYoeNFE8fLJpoNqQUMAyM+0Jmws\nuRmB21YDCUxJIEpaN7y8WvfcbuElVbQ1OBic6ej4V09ERDo/Gt49ovXUQIImJUEbSBACuGZMXwD6\n6Q+UPsoqG1B0z0dYv68mbtv81evrdM8LIuhAEit5mfrEzyaHG7e9uV59TETJaftB/VQGHuKi7+a5\naxI9BAojbCBBCJEhhFgthNgghNgihHjIu7y/EGKVEGKXEGK+EMIW++ESEVG0ON0SKo87ApbbLeHr\nIwCaqQ0pCskIAAAgAElEQVSaEyiXJqhwQpcsDCjI8SxnRkJaWv79EQDA++sPJGwM3fMyErZt/4yE\nijpfQcjaxsDvHhElh05Z+u+2U2J3ovbyz1xczRa5HV4kGQktAM6TZXkUgGIAFwkhTgcwC8CTsiwP\nAlAD4ObYDZOIiKLtj+9vxn++3hOw3G6NLFlNqSMnSYFTG340vDse+slJvgr1DCSkpUbvXXdbgtJ+\nrzv9hIRsV5Gboc9IcGoCbTWNzngPh4iixH/KlLZ7EbVNjSa4ekKXrIi6R1FihT2yyx7KZEOr9z8Z\nwHkA3vEunwfg8piMkIiIYmLxlkOGyyPNSLB4IwnabAMlYPCT4t7IslnUAosMJKSfP7y/CbOXfA8A\nqKhrjvv2Lx3ZEw9NGhH37WppAwmSJMOhKUC6p7IBizcfTMSwiKidsu36IKE2G4/aplpTwPLSk3uq\nxZu/K6vGnz7YzO5PHVBEtwiEEGYhRCmAIwCWAvgBQK0sy0oVjHIAvYO89xYhxBohxJqjR437lRMR\nUfwpRd/85dgja+ijZiRoDu7KHVelfoLZ2+uOgYT089q3+9THH208GPdU/ulnD1T/DhMlTzO1odnl\n1nUyAYDpr63D6j1M3yVKNnnejASLdx/jYCCh3arqPceIey8eCqtJwOmW0dDiwk+fX4l5K/fiyPGW\nBI+Q/EUUSJBl2S3LcjGAPgDGABga6QZkWZ4jy3KJLMslhYWFbRwmERFFm9E11sSTukd88WU2aGOn\npHcqJ1fKOiy2SA5XfE+0TR2gnLS2knuTw40WZ+Dv4ChPjomSTt/OmQCAf/58NABObYiGqgbPvvCs\nIYWwem9CHD7my2arDTId7M75pXj0422xHyAFaNVhVpblWgDLAYwD0EkIody26gMgcZWUiIio1YJl\nJERKCThU1vsuhH7y3NcAfIWolIACiy1SLPuBr93bMe/qCyHwh0uHAQCanG60uDw1I8490XdjZdm2\nwwkZGxG1nSQDhbl29OnsaZXskiT8d/U+vLVmf4JHlrz2HG0AABR1zYbFG0ho1gRfnUGyPt5bfwBz\nvtgd+wFSgEi6NhQKITp5H2cCuBDANngCCld5V7sBwAexGiQREUWfNpCQlxHZdAYt4X3/Kyv3Ym9V\ng27+olIpX7l4lBhISDunFXXWPY/l38CV/1oZs89ur27e70Kz0ze1oWenTPX199YfQFU9sxKIkokk\nyTAJwGbxHONaXBLueW8T7n5nI/7Ku+Nt0uKSYDYJZNrMsHoLLDU5Xerr8bgh0ex0Y9bi7Wh0uMKv\nTBFlJPQEsFwIsRHAdwCWyrK8CMBMAHcKIXYB6ArgpdgNk4iIou2QJmXwN+cPBgAItO2u8e7KBt0U\nh255dgC+1G6lej+lj7wMK0b0zsMlI3sA8NzBi7WCHBuG9cyL/YZaQak83uyU1OkdvfL1LSk/KK2I\n+7iIqO0kWYZZCLXo8NaKY+prL3yxGw0tvBBtLZckq5mOSqefY82aQEIc6lC8vmof/rXiBzy/4oeY\nbysVhL0FJcvyRgCnGCzfDU+9BCIiSnLtbc/ndEm6uwVK54de3juvFbVNOLFHbru2QcmhusGBZqcb\ntU1OWM0mnD2kEB9vOgR3HOpkFOZmhF8pzpRAgnZqQze/cWawzRlRUmlyer7LFu+dc21gHvDUPvHv\n7EChuSVJnQ7Zw5vJdePL36mvH6htQkmMx6Dso1tYPDMiHaAUERERJZpS2KitHG7JcP6iUpDq7nc3\ntuvzKXmM/vNSnPHY51i7twZWs0mdQhOP6S3KSSAAdJT6npk2z3eryeGb2pDrN5XI3s5AHhHFjyzL\nWLTxICrqmmHzHju1rQsB1gVqC21GwoDC7IDXf/vf0oBlr6wsi+oYlONGW7Mz0w2PXEREaci/H7O5\nnYUXHS5JrVr9px8PV5cX5HimOBw93sI6CWlgTZm+6OEJXbJ8gYQ4XNk3Odwd7vQvQ5OR0OSd4pOr\naQsJ+O5qElHHp2QjAFCLAiodBa4u6QPAU3yRWsctyWpGwsDCnIje88AHWwAAg7tFtn6k2nlKlDYY\nSCAiSkP+NQvaW1F/f3UT3l7rqVZt0WQ3aD/3OOeMpryrntcXPRzcLUe9wxSPOFJmB5wikKHWSHCj\nwfu9U7qaKJSe9ETU8V3371XqYyUIWNPoyUg4tZ+nyOzOw/XxH1iS02YkCCFw54VDAtaZMmelt3Ct\nG0X3fKQuz4/yPrTJ4fn8d9aWR/VzUw0n7xARpaFKvyrxFvXg3bbPe/KzHepja5CghH8WBKUWbbEx\nRfe8DPVvyh2HSEJuphVnDS7A1oPHUJhrj/n2IqEEN5ZvP4L3gxRVzOqAARAiCtTkcGPdvlr1uTK1\nocY7tSHL5rm0uu3N9bh4RA9dYJ1Cc7t9gQQAuO28Qci2W3DxiB4447HPAQDf7q7GNz9UonenLN17\no5XxppynHKxrAgA8t3wXrjq1T1Q+OxXxr5vSxnlPrMBLX+1J9DCIOoTKev18zvZmJGgFKxzHOEJq\nu+TpLwOWjRvYVT0xjFUg6ellO9XHeRkW3HHBEKy+/3y1BWmiKYEEbRBBW8uBiJLHsAcW654rQfgG\nhxt2i0lXK6ieWXit4pJktQsG4MlKuPnM/mrRZkWm1RLQnjHacWrl8/ZUNuDSp7/Ek0t34P31B3DK\nw5+qU9SIgQRKE8ebndhd2YA/L9qa6KEQdQjHm5265+2tkaA1pLu+O8O1Y08AADCOkD6uOKU3yh67\nFN3zMtQaCbHq2vD3pb5smLH9u8BkEgFdERIp06YPrF12ck+M7N1Jt4zfDaLk8/iVJ+vuoGfbLWqt\nIMBThJgiJ8n6jIRgtlTUoa5Jfw4TaUaCW5JD1mtSPqZZUwdjS8UxPLVsJ26fX4qaRic2lNcGeXf6\nYSCB0sKeygYAgfNSidJVQ0vsIuoFuTbd86Heto/xKLZHHYTmXFAJJGhPsKNFe2f/ilN649fnDIr6\nNtrLvyPDvurGgHar/GoQJZ+rT+sLoQnCS7IMp6bI4qINB+FKk2DCkePN7b5T79IUWwzlkY+2qYGE\nK07pDSDy84uB932MG15eHfR15VNC/SxT5nwb0bbSAQMJlBaUQMIJXbLCrEmUHhr80gKVNMFoFKvr\nnKUPJCinBbxYSh95mq4Eynnh3e9EvwXokWO+Wh9nDCqI6hSdaBF+2T55GYEBbZk5CURJZfHtEwKW\nZVnNulowDy/ain+nyZTaMX9ZFjDtI5hmpxsOV2CAxS1JEWUk/GJcPxzzBhLuvWQYLhjWHa1pkvHl\nzsqw6/gXpPbX5DD+GdINAwmUFnYf9QQSeuVnhlmTKD34F75Tovk98tufEm71Ly7lvZDixVL6GKRp\nxaX8qW09GFiMsb2OHPcFErJtyVGw8J6LhwIAFs44E2P7d0nwaIioLYb2yAtYlmE145KRPXXLKmqb\n4jWkhFEKEwLGtXAaHS7sOnJcfT70j4sx6dmvAtZzuYNPbdDe5LCZTWpGQn6mFSYRWUaCf10FI3IE\nx6t+XbMw7IHFmDJnZdB10gUDCZQWGrwFb9gXlshDOVi+PPU0LL3jLEw+pQ9+d+EQ/Ob8wVHflvq1\nYxwhLeTYLZh4Ug/1eSwLCx493qw+zrInRyOqE7p6MuNG9snHHUp7M343iJJChtWEW84aYPia3WpG\nQY4dz193qrosFU87ldaII/60BKv3VGPcXz9XX6tpdAasf9Pc73DB37/QFaLcfuh4wHpuSVbbafrb\n+vBE7H70EnTJtqHZ5UZdkxOZVjNsFhNMQkQUSDh6vCXsOkY3PL68+1xsfXgi+hdkAwD2VjUCgK57\nR7piIIHSgrJbcMZgji5RMlIOuif1ysPg7rmwWUy47fzBQTsutIcSwOO3L3XJ3iJZt547EJsfmqhr\nvajt7x3tzg2HjyVHRsLlxb3UxzZNxo467SfO4yGitnG6Zd13GACmne0JLORleIKZ2roo/lObUoFS\nrLm+xYWrX9DflddmJyi+3V0NADhU1xyyDbBLkmE2GV+aCiFgMglkWs043uxCs1NSC9maTQI7Dtej\n6J6PcOHf/xf0OKPNYHNGULviF+P6Yfejl6Bvlyxk2SxY/vtzMNlbk4E8GEigtBLJjoMoHaiH2Xae\n43xw63h01hQx/dU5AwPWEVDa/7VvW9RxNTrccEsycg3m/08YXIgMq+d0o9kZ3X3wEU1GgtG2Owrt\nybF26k8qXmQQpSq3JMMtyQHT95SCwgU5ngBqXqa2RkzqfcdDtVr8yq/+gDYjbcLjy7FqT5X63P+C\nf9OBOtQ3B2Y0aI3onYcPSiuwYscRVDd42lhrf8U7j9SjJUjtgocWblEfB6uBoB3SkO65AXV3jjWF\nHl+6YSCB0oKyY3C6JeytasAV//w6oHUMUVrxfinae5Izqm8n3PmjE9XnJ/UKnDfqy0hgJCFVKSmj\nyom0ltkkcN8lwwAEFvlsL22xRSVY0RF9uOGA+thoDjCDbEQdn3Izyr/rSq03nb9LtqfQcNdsX8Hh\nFIwjhLwpp80SA4DyGn2GwrUvrlIfa6dBSJKM6gYHfvDWNAvmzEEFAID91b7P9T+PMcp6+HpXJTYf\n8NU9CFYvwaWp2phlkOVW0+gIOb5003GPukRRpFzAfPNDFX7y3NdYt68Wn245lOBRESWOcpyNxjmO\ntl2T2eCsKVzXhkN1zcwWSnKHjnkyA3rkGRfrzLB4TsiWbj0c1e0eOd6Crtk23HruQPTt3HG78ijT\n6q46tY9uOYNsRMnD4T1OWf3m8St3xtVAQo4vkNDsjF2NmERxGVyoZ1hNyLVbIEPGsWYnKus9AYX6\n5uDB4+oGX9Ah0gv0Qd1yA5b5t4w0ajX883+v0j0PlpGgzZozOmfRBj/8/w7SEQMJlHZqDQrBEKUb\nJaUwGqnV2jusRu33lLsFRsWQGh0unP7XZbh/waZ2j4MS57ASSMgPzEgAgOPegrf3vhfdf+fK+haM\n6tsJd00c2iFbPypennoaAOC3fsVMO+6Iicif0u7PPyNhdL/OAICzhhQC8BScVUR7OldH4NIE/lfe\nex6+f+QibPjTj2C3muBwSRj/2OcoeeQzAMDxEIGE11ftw8INFaisb1GD0eH07hTYfS03Q19o97Jn\nvwTgyZSTZRlPL9sZ8J6moIEE33KjcxYlaAQYdKhKQ/wNUFowiiom4/0fp1vCwg0VIYvVEEVC+QuK\n9rWXUUaCcrVk9D1UTswWb2aGUDI7VOc5CewWJCMhVjduahud6JTZcWsjKM4d2g1lj12Kvl2MsyY4\ntYGo41MuPv0vIM89sRu2PDQRp3oDCkII7PzLxRhQkJ3yGQk5dgvsFjPsFjNsZhNaXJIueLBmr6fQ\n4pu/PB0TBhfoPuflr8tw25vrUfLIZ/h6l762QjBK1xutKu/F/ai+nQB4pj3UNjpw2l8+w6zF3+Pv\nS3cEvEfp5uavk6bmk9FuWTst2vB8J80wkECURCbMWo7b3lyP55bvSvRQKMn5pja0/0CojeybDa4Y\nQ21ByYhoTXBsS0Ud7pxfyoBaB1Ld6IDN7EltNWKzRLejwr6qRryxah/qmpzIz+r4gYRg2NGEKHnM\n+6YMAAynxmb77fusZhMyrObUDCR4pw5MPaNIV+S2oq4Z76wt1637j8882QBj+nfBDeOKABjXiXn0\n4+0Rb/+xK0YCAH5W0hcAcOu5gzCmfxdcOtLXdnj1Hk8A4/n//aAuO3NQAf4yeQQAoDHIv4s2SFSg\nmaKi+PNPTlIf+2dCpCMGEih9JeGZm5L6telAXYJHQslOrZYchYB6vSayn2FwwagECwwzg7wLjeZc\nBnPp01/hvfUHIuoJTfHR5HAjy24OOlXmitG+lllF93yEt9bsj+hz61tc2FIRuL/79Rtrcd+CTahv\ncenaSyYf3tEiSrTNB+rwpw8248udR7G/ujHoeoO75wAAbjijKKLPzbCa0OxKvUCC01uQ8JwTCyN+\nj9kk1HaNd144BLeeG9jhCQBeu3ls2M+aMuYEbHloImZddTIAYFjPPLw1bRy6ZPum1t3y6lrdewZ3\ny8ErN41Rs0YaW4z/XZQgyX+mluDcE7sFvH79uCKUPXYprhzdh113wEACpYlo9y6Pp6c+24kB936k\nu+vLwnTUXspXIhpTG7Qpgv5zRwFNsUWD6J2SVRAuu0CSZNz6+jq8sWqfuozfg47jk82HQtafybDq\nA0yPL47s7tNNc7/DpU9/FfD3oc2kSYapDeEk8zGKKNnNfHcj5q3ci+tfWo0Jjy/XHWeMDO4eWPDP\nSKbNjGanFLRDQLJSLrb9p3god/sVTrcEkwB+c94gAMAZA7vi9f8bi1+dPRB3TRyKK0b31r3n3V+d\ngTP9pj8E458BAiBk68jHrjwZJpNAts3zvmCd2zYdqEOG1YTzhnYPGSgwCe63AQYSKE0YfdWTpUr2\nk5/tgCR7DnSKcQO6JnBElAqUv/9oRNS1cwqNihOJEDUSlOtDd5gDcmV9Cz7adBD3aYoyMpDQcbQ2\nOyTSBBQlPbWsqgGD7/8Ym73ZWP0082Q5tYGI2qNnvr62y31Biv8qhRMzrZFN1cqwmLF2bw2GP7Ak\nZTqFVTc4cMf8UgCB3RImDNJnKByqa4YkA707ewokCiEwflCBWhj371cX4+dj+2Hujafhz5ePULMF\n2mpIiACP3XuTQ+mssftofcA6TQ43/rfjKC4Z0TPstkxCRHwcS2UMJBB1YNq5dR9uqFAftyYNnMhI\nNDMSbhrfX33sdAVe3Ie6WFICD+EC+1UNga2hnAYtnij+lAredoNslGCMAk6hvL/+AJxuGW97p0R0\n0fRpT+apDerXj3/KRAnTx691bLbNOFDQ5D0niziQoFnvs23RbX2bKH/79HscqG0CAFj8MhKUgIFi\nn3eaSO9OoVvznnNiN1x/er92j+2MQQV43DvdAQDGD/LddMuwesaabbegMNeum5KpULoPjR8UPivC\nZGr9cSwVMZBAaSFZv+tlVQ2Gy1OxeA/FVzSLLVrMJqz4/Tn48aheOLUo8I6Csg2jNMBICyYaZR8w\nI6Fj2F3p2U89OnlkxO9p7T75mc89BWY7ewMI2n/7/MzAgljJgnNsieJjT2VD0FT0Fr8AeLCbNcoU\n00iDpnarbz2HQZA9GWl3WVa/4sr+RRR//u9VAAIDDLHUVxMU+ufPT1Uf28y+oE6WzawGhbSUOmTd\n8ozbGGsJZiQAYCCB0lgyBBeC9bkNtpwoUr6pDdH5vKKCbDxzzSmwGxZbVLYZKNKIvtGJnYOBhA7h\nyDHPtIY+rThZbOudnK7eQILD5Xt/MmckKJJlqh1RsqlucGDD/lqc+8QK9L/3Y112p6LF76IyWJC6\n2elGhtWkpuaHow04pMo33KQ5aTDqvvDKTWMC2jz6Tx2JpdH9OuE35w/Gny8fgTxNV4UMm+/fIsNi\n3E1j+fdHAAADCnPCbkfAc3PE5ZYw54sf0vYGHwMJlBaMTtKSIZIYLIKdilWAKb7Upg1xuCGq3HXd\nbNBtRIowFuAymMZgNI2CwmtyuHHLK2tCVidvjaP1nrs4hbmh7+IorbqAtgdy7d5UYW0QKZK7Rx2V\nWog0CY5HRMlm7d5qjP7zUvzl423qsn8atM9udrkxqFsOXr15DM4Y2BWSbJwt1+R0RzytAQDKa5rU\nxx+UVqhTApKZNpDgX2wRAM4aUohzNN0Ofnpqn4Biu7Fkt5hx54VDcP3p/XQZXwWajg4ZVhOanIHn\nD7uPNmBAQTZ6dwofFPfUSJDx3roDePTj7Xj28/Rsy85AAqUFo5M0/5SsjijYHPCq+sD54kStoaR4\nRmNqQzjKFn7739KA1yLPSAg86DMjoW0+23YYn249jMc+ibxvdyhKocVwgYSenXx3pYzmp0ZCCSg5\nXRKGdM/B+j9eiLyM5M1I4MwGoti58l8rAfiKtgL6C2HF8WYXbGYTJgwuxITBnoKBRlkJTY7WBRIa\n/PZzD7y/OeL3dlTaX59/sUWj5dqaBYmkzSKxmE1wG5xT1DY6Ig5Mm4Qny0TpyHEsRMeIVMZAAqWd\nd6aPA5AcRVIc7sDMg2E98/D59iOc3kDtEt+MhOCvhevWoDDKSLj+pdX4ZNPBtg4rLTlcvlZk0Qqm\nPvHpDgBAjkE7Lq0bxhXpnh9vw4mXcvLncEuwWUxqzYRklwSHI+pAtBeoTreEFd6UbPL56yfbDJf7\np+Mv3XoYX+6sxNaDxwD49otGgYRml4SMIIUYjTS0eM7Tpp01AADQvyA74vd2VNrsAqMWjID+d9wR\n68CYhTDMOKlpdKJzVuTHlNpGpxqgSIZrilhgIIHSgvL1vuikHmp13o7e+UCSZCzcEHiRdGq/Tmhx\nSUF74BKFs3TrYfxtqefiz+juTLSFynqItA9zsKKMc78pa8uQ0tb5f1+Bme96WpsZpaW2hTIFK9wJ\no7bwGADD/Vs4SpaW0y3BFqXxJ5JaiDTB46DksX5fDU760xL85s31AIA5X+zG1Je/w/LtDCYoZFnG\nC//bbfia/7Fk9hJ9ZpayXzTKCG1tRkIPb22AK0b30T1PZp297XZz7RZ0zzP+eYJlKiTCM9ecgnd/\ndYZumckUOK1SlmVU1regU4SBhHkr9wIA9lU1et/vWe50S2ono3SQ/EdhogjIMlCQY8fz15+qRpsj\nrRafKG+t2Y8F6w8AAP4ztQSDu3mKvygHsVSpAEzx94/PdqiP43G4D5mREOGfcbDiV8HuiJDPv7/c\njbV7awAA+6t9c3T9L+zbKj/TihvGhW/dZTHpt6eckAZjtI9WlrW4pKgFQhKpA96sow7unbXlADwt\noT/behi7j3q6pih31An44wfBpxD066pvRTi2v6dF4Gd3ng1AG0gwyEhoZY2Ef/ysGM9fN1rdZipM\nx1MCLN/ce17QdZSMhEhqDcTaj0f1wqn99N2kzCYRkA151zsbUdvoDHtc8ldR5zmmKoer0X9eikH3\nf4I9lcZd11JN8h+FiSKknLApJ7NGqdIdyfFmX+ri4G656viVg1yDo21zjIm0F99xmdoQ4jWj2gdG\nggX+slqRZpqOdh05jkc+2oYbX14dkP3RMz86J3luSYbZFP50wn8qRWaYfzvtibxyYupUpja4PFMb\nUkWkmTlE2guU/3tlDd5d5wksHKprTtSQOpzXvt0X9LVPNh/SVdiXIaNrtg2DvDdrlP2U0c2aZqe7\nVQHYztk2XDSip5o9lQo3gBodLphNIuRUNiXzoqNmzpoMpjYoAbrWTG0AfOfkWys8xaSVc/efPv9N\ne4eZFFLnKEwUkm+HYY4gI6HF5ca5T6zARf/4AjsPH4/56IxoW5pZzSb1pL+m0bNjfnjh1oSMi5Kf\ndo5jPOYvBttEWWUD5n+3P6LP8O/zrUiFE7NYWvlDFQCgU5ZNLYqoiNbUAJckRVRvwf9vLVwwVxtI\n+PnYEwD40kdbXJJhq9FkxTACRcoS5Ht7+BgDCYorRvcO+fqybb5pIC63rJvTrwQojTIS2jqlymQS\nsJpFShyvvtpZCbckhzx3KO7bCUDbi+rGmtkk0NDiwtKth/HNrkrda61tJ/y5929pQ3kdfvbCSvV8\npzJNiqIzkEBpQ9nlKXO3QkVKX/lmL/ZUNmD7oePYZNCyLh6e1bQosllMeGpKMf7201HqTm7N3upg\nbyUKyR7nO7lGc03XlFXjnCdWYKFBT28jwQrzpUv6YFu9+q1nHmdepgVVDfoTG2eQbJBmpzviO+Se\n/tmSYT/xcIJNV1EogYbfXTgEf7h0OABfALihxYUce/IHEpSTTiYkUKSygqTWBwu2phNJknHvexvx\n3roDuuUTBheg7LFL1fOn/TW+1rcuSdbN6Q9VI6E9U6psZlPS/xuVVTZgQ3n4c+LcDCtuO28Q/jO1\nJA6jaj2zENh5pB6/fGUNrv33Kt1ruRmRTZdUglXaemur9lSr+/LWTpFIVgwkUFrQnqQpJ7zPGvQS\nVpRrDjKJqqWwT9Pj3WYxoVOWDVee2gcZ3rS6jBS6G0fxFc+ezoA+a0CWZRw+1owdh+sB+DJsRvTO\nC/kZx5qN72wwnTc05fdcVe9AjV8gwSgjYP53+zD0j4tDzjHWevRjT6GySLtvaFXUNYe8i6oEGrrk\n2HSV1OtbXKhucCArBepjxKP9KqWHSKeJpbJ1+2rw5mpPltsZA7uqy1+9eSwA4J8/Hw0Auta3bknW\nZXmEqpHgdEuwtjEQb7OY1GPhx5sOYktFYm5StYYsy7j3vU1YsuUQ6pqcOOeJFQCAF64/Nex7f/ej\nE3He0O4xHmHb1Ia4kZgXYUbCHRcMARC8W0OWLfmPT5FgIIHSgiz77vyYI0jl1qYkdYSWLtq04Vu8\nbYSuPf0ELNt2GC9/vScuY5A6eHFKily02v5FSltg6tVv92Lso8sCWnNtPnAMz//vh6CfcazZCZvF\nhOE99QGH4y2uNrURTBdKiunBuuaAOy8trsAWslsqPAXblDnGzU433ly9D1/uPBpyOzsOtX4K2J8X\nbcXYR5cFfV35u7GaTWoa7TOf78KIPy1BfYsL2SlVH4P7V4pMsKCd0mownf3+7Q3q4zm/KMGS28/C\n3BtPU5eNG+AJLlxd0kdd5p+RYFFqJBgGEuQ2TwnTBhJ+/fo6XPr0V0HXrWt06uo4JMqqPdV4c/U+\nPPDBZnxY6snyuGBYd0w8qUeCR9Y+pftrA5aN7J0PAAGFGYNR6jMFyzJpTJM6ZgwkUNpQ7vyYIkjB\n1d4lS1SbyItH+HbU2gNXls0Cm8WEFduP4uZ5a/DQwq0xL9RVWd+CAfd9jPnfBS9gRMmh2enGqt3x\nnRbTojkheuCDLQD0xUQV2rtE/o41uZCXYcHC287EI5ePwNaHJ+KpKcUAIs9KqKxv6fDdWqIt1M9r\ndOHhf/L6f/PW4N73NuH6l1YbfoaSvhnt+aCbyutw5qzlAHyBL/9dd7Mz+e/AcmoDtVaw431HLWwX\nT2VVvkzObJsZJ/bIxTkndlOXmUwC3XLtuqlYbkk/NUs533IaXCA63ZHVgzFis5gi6togyzJGPfwp\nfsWFFcMAACAASURBVPXa2jZtJ5reWuPJ7hh9Qmfsr/F0J3j22lMSOaSoMDouDu6Wg75dMiPO2NQW\nrR7aIxfTvDf5AE+gqsGR+EBQPDCQQGlBbuXdHm3KbKLuxDc73RjWMw9bH54YUNTG4ZLwvaYIZG1j\nbE8gqrwXCaGmg1ByeGrZThyobQq/YhRFo+VVdYOnv7PZJHDd6f2QZbOgW66nMvTL35SFfb8kySh5\n5DP8+vW1Acs7wp2fWAn1sxndMWn0nvx0z7MDAL7yK0TlTyl4GO3foTY7RUk19q/DcDAFprWw/SO1\nlv9F0LybxgDw1IupbUyPAm9GtL+XXvkZQYsB5mRYcKzJt+/zL7ao7G+MMxLa3i3GbjFHVGzxv94C\nxMu/D50FFg/HNMGpA7VNKOqaFfepkbGmZLZ5MlMi/7e1W0zq303fLlm4YLhvGscJXbLgcElh6wCl\nAgYSKC1opzZoFd3zkeGOXZZlFHn7/pbXNBmmQcVas1NCjt0c0TyrsqrYFpxTAjFNjtTfKaa6wwm4\n+IpGpeofjjagf0G2bpmSWvjGqn0BHQn8lXvvpizZcli3fNaS7Rj6x8VJGUyQZRn3vLsRa0MUXm02\nmL6gMLpjotzVNLq7uXz7EVz/0irdCXsnb0bC8F6ha1y0lrY1pHJy539hEK6uRjJhQgJFSlva5OQ+\n+Th7SKH6vLJevx+sqG0ynMKUipo0+/B3f31G0PW652bgkDfrdGvFMXy69bCugKJyXGk02D+2p9gi\nAHy06WDYzM5739vU5s+PNmVX3+x042BtE3p1ik7L4I5iwuACDO6eC0BpYxx5ZFdoWkj265Kl1i0r\nyLGp5+2NaTDdiIEEShvBdg9NBhcQTrekRl1f+GI3Ln/u6xiOzFizyx1x5DfWBeeUomxNaTLnK5Vl\nJGBeeXsrVTvdEsoqG9Q+3wrtQf/VlWUhP+Os2csNl7+zxtM72miqRUfX7JTw3+/248p/rQy5TjCN\nfq25ZFnG+n216vv8A6g3zv0OX+6sRL3md9Upy4osmxmPXXFyW36EoLS1bGwW46kNM84dFNVtJoIy\n5Y5TGyhS2qkNXbI9Pe//esVIAPqitA6XhDMe+xy/f3tjfAeYINpaOUq7bCPd8+xYu7cGu4/W4573\nPL8bbXeuHG9GaoNB68K2tn8EoBa7nfluxwkUhKPUCGt2Sqisd6Aw157gEUVHz3xPNqPZJNSf0SVJ\nuloZrXFC1yy1ELrFZFKzVr5PUPv4eGIggdJCqHM0V5CCOvFukadV1+jE+n21YXdqf5k8AoAn5eyj\njQdjNh4l6pqoehEUPZWaO/cXDItPReXWZiTsr27UpehW1rfAJcno01l/cqi9+CoIcoJz+FhzyDoB\noSp0d3SR/F5DZVr410hwumXUt7jwi3H9AAAflB4wepuubaQkee6KZkYYoJp6RhHuvHBI2PW0+5qa\nBs8FghJcyLKZ8f6t43WV1pMVpzZQa2n3Z0O8d1OVAnFlmna4yk2Sz7fps7BS1e6jnp/9roknhlxP\nCWxf+vRX2GjQyjA7ZCBBbnNGgv8x5uQ++QHr+E+l3XUksReiakaCy42q+hZ0zU6NQMLi28/CN/ec\nB5PwBBKWbz+CJVsOY6+mxkZrWEwm9cafEMD2Q56ixbe9uS5qY+6own4bhBB9hRDLhRBbhRBbhBC/\n9S5/UAhxQAhR6v3vktgPl6htPFMbjM/Y/HsFV9a3YO3emoh65cbKq9+WAQg/R06JnD/68Tbc+sY6\nfFcWmyJ6RgGE37+9Af9cwZoJyUab+vrvG+LT4/mSkT1btf6Ex5fj/L/9T32uXDD7tzw9sUeuGvAz\nuqg+erwFYx9dhseX6Is4ak/WrN673dGYfhFv4WpP/O6tDSEzLRr8MoyUz+vbOQt9Omfiy53G9RG0\nbSPdcuvSQR+cdFJEmQTabjlKqy6Tdx8+5bQT1G4UqaK1dXwofWkDCcrd8YGFOciymVG6vxayLGP1\nnmrUey+EUyHgFonvvZ1jri7pG3K9bt6gszYb9fnrfO0MlfOqP36wBfurG+F0S3jxi91ocrjhltoe\nSPBvYWx0Tur0a+H5+fYjbdpWtCjZLzUNDjQ43CjItSV0PNGSn2lFr06ZqGtyYvOBY3hvvSdobpSh\nHAn//ffY/p7uIN3zMto30CQQybfBBeB3siwPB3A6gFuFEMO9rz0py3Kx97+PYzZKohjyv4BYE6OL\n8dZQ5lcFmwM8wDtXXDmBV/7/trfCbrQZ3dF9Z205Hl/8fUy2R7FT3eBAr/wMvH/r+Lhtc1TfTvjk\ntxNa9Z6qBl9GghLss/hVy7ZZTNj80EQAQJPBfFbljtInmw7plmt7SCsnhaFqCXRU2kCCUSX3d9eV\nG75vaI9cdM22YUvFMV3GgrIvtJoFCnPt2HWkHkBg5or2zppbktUL/EhF0jlHG7y8arS3VZv3bTn2\n1Cn2pfwmOLWBIqX9W1HqI5lNAo0ON15ZuRfPLd+Fq19YiYc+9HTISZduDuU1TciymVGQE/piNz9L\n//rr/zcWF2m6ZCkp6oCnk9AHpRX4y8fb8ORnOwD4gs/tZvCld/nd2Fq08aBhZkS8KENUumEUpEhG\ngmLt3hoAwMINFQCAvIzwNcmMyLJvmtGN44tw2cmemycl/bpEYZQdW9hAgizLB2VZXud9fBzANgC9\nYz0womgKdbfH4Q5M7zX8jDie6SlR0ddvPt3w9Xk3jcGkUb0wopcnNU4Zc6zmeX+xw5MZoVwvrN6T\n+GALtY3DJWH8oIK439Htmt32OxnKhavR3FRl+o/TINilpBruq9anK2pPzJTPNApEdHTa9mQvfbUn\n4PUBhZ6Ao7Zn+ondc7H49rMwwtszW1vYSwkk2Cxm3dSu/gVZ+u36BTBak5FgxGh6mTZrJN9b0FFJ\nSda23Up2nNpAreWWfdO8jPbjT3zqueD9dGt6TGlQSLInWyBY9qni/yb01z0fP6hA91z7/t2VDeq+\naM4XuwEYH4ci4X8MNDqj9M/+3Fheh7Nnr2jT9qJB8jvv7RomSJPshvZoXQHfa8acoD7OtltQ9til\nuOWsgRBCoGu2LeD6IhW16tsghCgCcAqAVd5FM4QQG4UQ/xFCdA7ynluEEGuEEGuOHk18KxNKX8GO\nLQ6XfkcZbK50sABDLLQ43RDCdwLtr2+XLDx9zSnI8YuexqryvH/bx6tfCF7cjTo2RzvaV7VHp6z2\nBxKMUkqFELCYhOHFaDDaO/lqRkKIooQdlfbneOSjbQF3Hgtz7BjTvwv+fPkINatA2acoe7ON5bVY\nU1aN9ftqcPpflwHwZHrsr/a1CN1TqQ/EaItnumVZVxixLZoNppW4pMBljhQMJCiYkECRWru3BhW1\nTVh9//m4abzvovjy4l6G659zYqHh8lQjyXJAQVYjeRlWjCmK7E5xeXUjPtigrxXT1uPnkjvOwihN\nXQSje1PKcWzmRUPVZZX1LZjtNz0vXvwDCXmZxuekqeLJKcWtWj/Uoc9mMSXllMnWivjbIITIAfAu\ngNtlWT4G4F8ABgIoBnAQwN+M3ifL8hxZlktkWS4pLEyPnRl1QH477EcuH4EbvAXF/OcZa7/4uZoT\n1nimPnv62YY/IvqvE+uLoWS82CK99ravaqv2BC+CTW1QmE3CcPpNsEwk7Xfc6v3MpJza4HeScviY\nvntLs8vTfcZuMWPyKZ5Ewk7eE0Fl31bd4MBVz6/E5H9+o74vw2rCgVpPIOH560YHtJd9fdVe9bFb\nimyqQihG2SChCmTmpFQgQenawFAChafUuJFkoFtuhu67948pp+DC4YEFdFs79ShZeQIJkf2ss66K\nrMvM8RYXvt5VpVvW1uNnQY4dH8w4E29NG4ee+RmGxyclIyEvU7+Pe275D23aZnv574Z7pPic/175\n0fv5bBZTuztWJYOIvg1CCCs8QYTXZVl+DwBkWT4sy7JblmUJwIsAxsRumETtI0MfObzu9H64wHvA\nvfy5r3HxU1+qrynTCn48qhcGatrNHYvxPMPaRod6Qu2WZLV3eij+KcXR7Be9paIuoIKwMgdMmUem\nVIqm5OF0SwntSNIWoaY2AJ4TO6OMoWDXZhc/9SVu/+969b2AJwso2fifpPj3PZckGUrs5Zi3NVq+\nN5CgXIzXNAbu13pqTqZG9+usu+sJQNdL3LONdmYkGPzujXq4K1IpIyFNrvEoSu4J0zrQahBsVZYc\nCdPBJtlJIYpq+yvqmoVe+Rlq56vWaG8gfkz/LhjeMy/g+CRJMq558VsAnsLC918yDGcPSfANWM0Y\nH7hsOPp2yQq+bgqI9O/Hn/af8n/7/4fSI6WwmU0JrW8RL5F0bRAAXgKwTZblv2uWa8twTwawOfrD\nI4oeAf0OQntRsu3gMSz//gjKKhtwrMnzxf/71aPQW3PCHOuCRcUPL8Xlz30NwHMHNpKMBP8DWrQy\nBtbtq8GlT3+FJz71FFNUqhz36+o5iCgXIW2dK0iJ40hQRoLW6BOC12fQBq+Ui1+lAJU1SADEYhaG\nqfD+aZla75dW4D9f7cEqb72PtlZrTqQHPtAfdv0vyCVN/QLlTlcPb5Ag1MW4tge73WLGtWNPQK5m\nGpW24FaLy93uqTLLvw+sTK5UYL/u9BMCXkuljATGEShSTreEz7ytHLc+PNFwHaMbEG5ZxpHjzRjz\n6DL8fWnqFkiWI5zaAHguGL+593z8fGy/Vm/HKFjTWkIEBrqPNTvVFpa9OmXil2cNwK/PGQhAnx0b\nT9pj6CDNjTXymHHuIJw+oAsmneybVjTj8xm4/pPrsfNIPT7bdgT/25Ha0/ojOfqPB3A9gPP8Wj0+\nLoTYJITYCOBcAHfEcqBE7WGUNup/8nvjy9/hnCdW4FizE9k2M6xmky6VOhaBhGanG/ct2IQab4X6\n7w97Tp7dkgRzBAergEBCFDISXG4JV3jTnP+54gc0Ody6TAnAk+4HeE5QKHm0uNyQZCQ8I2Fwt9yg\nrz286P/ZO+8wKaqsjb9VnSZHZsgwMOScRJICgiCoGFbXNS+6KoY1LooJEV11XcN+ht01rQET6rKi\nZEGC5JwzwwAzMDlPT6eq+v6ovtW3qqvTdJ6p3/Pw0F1dXX2nu+rWvee+5z2HpccjXl4NwKVI8BRc\n07OMaolS5elJzAfVPise03YOna+TPVcGEjhekFZYbhzeCQ9f1gMPTBBLL3pzHieBQ8B1rix7+BLM\nu1os2ER/1w1Wh5tXS6DMXXxI9ry83orKRhsendwTL85wXzHs2bblDWi1rlTDF2ar6/omlZ2UqKV/\n1ZjtKK0VUyJa8qSG5yOTxhGaBRTGLbGhgVq9znH2wRd3z0Z6ogGXRtDnIm/OUuTNWQpADCRkJBkw\nuns2BndqWSV3AeDTmRcF9f4OGYn49t7RHv3MAGDzSfUyyi0Ff6o2bBQEgREEYRBd6lEQhNsFQRjo\n3D5DEIQLkWiwhkZzUKY2AJ7labVNdslQpqTWlXMcjtSGxXuL8fW2s2517h3NTW0IwWRIKXX+atsZ\nabXWwQkQBEGSa7VkmWRLpLpR/G2zouS8TCalpLwWGSyN6JqJfu1Ft+TPNhdK+xMPAJsXs0VAXIXz\nx2zxjRsHe3wtXEalkUQZDBEESCt0CQYdHp/SG4lGsZKFtwE3XXeeDJo7ZyXhqsHiqgtHqT/qLY6Q\nKwRqzGJgNT8nRbUiRJuUllOCjAR6vFUW0tAAXAsFL13TP6D3VTZaYee996EtAX/NFpvD8ZenSY9D\n8R2KigTXNS8IAv669AgAMbUsnwp6d81OwtZTlai3RLaMZ5NNXHgY2DEd39w7yutkOV6Z2DsXs6f2\nBgB8c496lbRgSQ0y0B7rtNweRUNDgfL+4mlVtq7JLuURlzuNjcTtoc91IvcR5YTc4WdqA80V/duF\nxCNBeYxGKyetQFY0WNFgdUgGPFogIT5Yf7wcw176BbO+3AUAyI5SLWgyiU1w/t8xIxHrZ0/A53d5\nt9ghqQ2eJPRiaoNvRUJedrLbPoR4TG0gkIGQ8trlvZRm9ORrsOf5ywG4Aq+0mZtekSbRYHXA6uAl\n75RA6N02VaZ86Pa0uApmsXM4fEFUWpDynYSF947Cgrtblh2Tltqg4S9EGehNAXRYoVICgNI6qxSU\nNSgWKOwcjwNFtSFsZfQIxCMhEP563QAY9axUcSEUVY+UrVy0uxjLD5YAAL6fNVr2d9w8sgsqG23Y\nfKoSkeTQ+VpnukjL7qVmjc/Hlqcvw+j87LAcP9GDeqiloAUSNFoFarJRTzfjVYdLkZYgBhIaLK7g\nQThSGzz1zw4+8NrsHTISVd3PA0Vp4FbtXB3MTTWhrN6KBVtFx/Zko04LJMQJd/5nO6oabdh7rgZA\n9GpBkzM60TlBzE01oWt2sk/zPL9SG9TMFhWrvCY9i4cm9lA9RijUPOFgW0Glx+uM5OpeOVC0LHrk\n270ycydOEDwOrD1VWsh0BgVWPnopXrluoOw10id9trkQp8obJMVW27TAA1MrH7tUFkAiffTGExVY\nsEXsY5RVKS7uno1LerbM6k9aaoOGL4j0PVERYKM56vQWobE5eJx3VmFRpj68+PMhXP3eRpyrMru9\nL94QBAF+CDkDhvgoDO0imkvnNqO/U6L0SPjbCpcqtVOm3NBwSGcxpUBpfh0O6M84V22GAIRN5REr\n6FhG5gsUOsTvMj/H8wJGS0ALJGi0GpQD6nQv9XBJakMdJSULp9michDJ8XzAhj6JRhYWBx90GTHl\nhKrK6d8wyJkf99XWs0g06DA6P1sLJMQp2c1YQQ4FZGWDrDTTl6S3RQ+fqQ06VtVsUXkpGPUsRuSp\nVxqJxXN57bEy3PThVlm6B4HjBfCCaPZEB0UfXbhXeiwInpUHvgaHvdqm4paL5UaHJN3qTKUZk95c\nj8lvrQcAtE1tXskstQkRJwi4YkA7AMC4nm2addx4gvw8WiBBwxdF1eJkXznRpBnVPUv2nMiqH/9u\nHwD384yUNrRxPOotdnyw/lRM9oX+EEj5R385+VdXSsPT0/vg63suRp92aUEflwEjC3SX1Yvq1wyV\n9AESwI3Ez0KXQ7fa+bB8py2ZBluD9PjFa3rgvku7Y0Lv3Ci2KPxogQSNVoFa/+stqk9q+NITl7Ao\nEpxrtErTQnszFAmJBlEhsO5YOY6Xuq9K+AuRR3868yK0S0vAT/vOAwD6tRcN8oprmpBgYKFjmbgd\ncLQm1AJLzZGihwISzCPKAn8nT0v3ixY8HlMbPCoS3PfzdM6qpUZEm6MXxOu4tM7i9tonGwvA8QJM\nelaWArC/qEZ6zPGec4abMzj0tNqX28za4iTVhaaywSY5hQfaB8YjympCGhqeaHSaLXrLuSYlmR+/\nvBe2PzsJC+8dLXt9S4FcHk+8n1iGwdOLDuDV5Uexs7AqlM2OGLwQOrPF1Y+Px4K7R8r8Ykx6Hcbk\nhya4SSsSaC+uNY+Pd9uXdIORMLemFak2jgfPhyddJN45V38Oz296HrVWeVrQ0SqXsuTygWl4enrf\nSDct4miBBI1WgSAIbsM1b51jsjOn6YdZY6RtYVEkOJuw7pjLSfnnfefBcf6ZLQLAjw+OxcJ7R0mT\niZmf7cCUtzc0u0nkRmLSsxjTw5UzRkuhTXqdGEjQltFiHrUJckZStBQJ4v+BrrAQp3GPqQ0ePRLk\n2xiGQe926hUjOBVFQ7QhpoNqq1TvrDkJQPQtoYOi9ECaFwSPKQwknYQYXwLAur9M8NoeT31Sc1Ib\nxM92DySU11tBFsU8qSlaIlpPquELslrsLUefTHRH5GUiNzXBrVKNEjKucXC8VHrQU5ndWIcXBK/K\ntkDokZsS1jQqhnFd8xdqxbST/JxkZKsYyZI+PRi16e6z1ThT2ehzP9rQkSgSWlE37BcO3oHpi6bj\nx5M/Yu6mubLXGuwuRUKNtUb51hZJfPYWGhrNwUtnqFyhJRMdetKhzNcNloU7zmJXYTUAV/oAAPz5\nmz1w8Lzfq3FDOmfg4u7ZHstBBYorkKCTcvMAoF/7NFw5SMzFLqmzQMeyEcnZ02g++87VoOezy2Xb\nrujfLkqtcQ2IyCpPoJN3TwNcPctKPgo05Oyc2DsHk/uK8sJOmUmSoSBNLCoSjjjznTNVAj+3OtMO\nbrm4K3Qsg3duHgpANLAk8LxnWerto7pi9tTeuO/SfGlbXhvvkw5PXVJzqzaoqcLKGyySIiEc+c6x\nhiu1IfDz7/PNhdhfVIPqRluLyHHX8I6Nujd7YmyPNjj44lQpoKBmKr3heDlqzDaYbQ6p3/v1aJkU\nVIjX+7oQQkVCuGHA4GRZA06W1Uu/60vXuJe6BVx/UzAK0Ov/uRmXvbne6z5WB4dxf1sre05X/tEQ\n2VO2R3p8vPq47LXyJteioFKt0FJpBbdpDQ3fqz1KvwR6Ek+cekM90XjqvwewcOc51dccvBCwR0Kw\ntdwJVqd7vUnPSivXgztnYEr/dmhHSZh1TGxOvjRcvLb8qNu2F2b0i0JLRCRFAiN3/wf8S7fwVL/b\noFNPWSBzs+uGdcLHd7rqRWeqfFYspulscCoxaNUAgZTObJcuXpNXD2qPtmkmdKADCV48Eox6Fg9O\n7IEbhnfyuz2eVFzNlb6q9XGNVk5KU/FXldUSaM7Z98JPhzDjvU24d8FOXPL62hZRwlTDM2TC6atq\nAB3YU7s27/jPdgyZ/wsuf8ulXHx1+VEUOw0ZHbyAX4+WwubgwfECZn+/D0dL3KtBxBrhLP8YLma8\nt8m1eKPSzwOBK/ie/GEfVh4qkZ4TlQG5xzXZONW+Ysfpatlzq4OHAM0jQUlhXaH0uMnRJHttwznX\nNVVr0wIJGhotB0FdkEAmL8kmeYSfllAvfmgcBnVKj6j0mWuGR0JqiGq5k5tagoGF0TnQz3HK7a4b\n2hEAkGTUgdU8EmKeohrXKuWs8fn4dOZFYXIn9g+lRwKt8umarW4gRp9jnlIbdJ48EpyRBH+upFgO\niqmILaQgCeknGIZBRqJR9p1yfriYd87ybNymxqrHLgUAZIagpjjDMLLjdMxIhMXOSSlT8TYpaA6h\nGKOfLBPltCQFSKNlQvyLPAVUA4UEDpTsPluNuz7biV7PLceRC3X4flcRHvp6j+q+kWLloRLct2Cn\nR+XOP9edxPKDJThe2qD6eqxR76zAYbZxMhWoGqSP4P1ULX23swj3LdglPS+sEMcB5P7Zd+4KmfKA\ncNsn26THiQYdrA4+pL4TLYU9pa5rwcK5/C1+PvUz1hWtQ79scbHm9e2vR7xt0UALJGi0GtQi85/+\n8SJ8NvMiN2muMq9Yx6rnYCv5cU8xzlQ2YsGWQiw7cKHZbf3tREXAq3EhUyRQNzWTU3pMTNEGdEzH\n/Gv646eHxnk1rvOXfedqcM8XO1Vl6RrBU1pnlR4/dUVvTIyyezC5zkbkZeL6oR3xt98Nkl7Lz0lR\nfU8d5U3iKbhm0LGwq1VtcP7vzziIUwlExApqUmO1ybbJwGLFoRLM++kQAPhdA3zW+Hx8NvMin/sB\nLm8Fo57FvrlTsG/uFL/e54k/XdJdepyVbBQHr06TyNZg8kV+n2Dk5NVm8RoprlafGGq0DEiQMFC1\nImFktyzfOwGoanClWp6uEPPqk1SMUSPJfQt2YeWhUrfy1ITXVxyLcIuCg/bc8qU0CbaPKKgQgyt0\nsL6iwSrbR3lsk4GF1c6JwYuW3w0HxM8FP0uPaUXC98e/BwDYefG3pdMcWjJaIEGjVaCsJ08Y3DkD\nE3rnwqiIBCvlwJ5c4WWfIQh4dOFezHhvE55ffAgPfLU7qDYr6z37wpuTcyCQVQ+TnsUlPdrg/gn5\neOFqlxz+jtF56JGbIpktbj9dhZeXHG7WZ13z/ib8crhUMnnSCC306nQsTMo+vnMEnri8F7q1ScZb\nNw2R5eQrSw0SqsyuQa2nv8GoY1U9TMgCjj/O+LGoSCCBE9rU1MHxaLJxLh8B6jshg31SLpLz4pFA\nM2daH79LVJHARVayCelJBqQHqUygFREmPYuC8gZwQuCKrHiFVAYKRTC13uII+hgasYuV42HUs83u\ny9une6+u0re9WNbw442npW1kwqtmjBopaBVCo9X9HHfE4UIEHSAnaQYJHhQJpC/8YEMB3l97El9s\nKQzos4qcAUZvZUPrqe919tTeMOpYWB08asx2pCUErz5rqfACL3kh5KXlAQBmDZqFuwbcBQBYVrAs\nWk2LGFogQaNV4CuoqpRMqykSfK2+E0dltUhzcwh0IE2rKryVtvSF1e5SJOh1LJ66og/aqDgJ61gG\nPC/g9x9swccbTwflKByWihgaMUfnrCT8eVJP1YGwSa/Da9cPdNtutvrO+0406tBkc9+PBBD9UiTE\nYNUG0ufQfc+sL3eh79wV0goSHShIMckHfHwYjLLapSXg6Wl98PGdI0JyvG7ZrmBSvcWB87UW8M1I\n7YpXyCqkp5XWQLBxmkdCS8bm4GEKIq0hw+kFde+l3fHIpJ7S9gEd0/DB7cPxxo2D3N7zj9WimVxz\nDVVDwb4iV675/mL3vHNzHHqD0GOeRps4iVem2BJIF3+6ohF/X3kMcxcfctvHzvFYsKVQdczZ4AwS\nGHSMm/LAbHPg8YV7UehUnjw4MR8PTuwBk4FFbZMdVY02dMxoXnnflkq7ZNGw+qEhDwFwVWdgGAa5\nibmYkjcFHVPENOAvDn8RnUZGEC2QoKEB99wzZWDBoGPh8DHRsNjdX7/1462q+/oz6Q7cI8E1ifDV\nVk/UmG2Y71QXeDL+IegYebpHoCu69HfQFIcDgVhHbWId63TMdPdvaFBZgVKSbNRLgzEalyLBN7Go\nSCBsOF4ulQhbfaQMgMt4i+4n0ihVkiAIcHA8dCE2LGQYBveNz5dVhwiGvDauVbKR3bJgc/Coszha\nTelH4qpvC3BVVU3mbFW5B/miweqQJhEasY3Nwfu8L3uDGLQyAB6YKFZrMepZLPnzJZjav50sKEmM\nlSucaQ7tfKgZwgldtnDmpzuw4mCJ7PV4vNfJAgnOYHmyh2CNr76Q5wVM+7/f8PziQ6pqhX+t++HV\nhgAAIABJREFUOyXuJ8hVS1sLKjFw3ios2lOMa97fBMClWkg06KS0lmj6KsUiuYm5GNNhDLqmdQUg\nloMExDSHBL14ndzQ6wYAwNDcodFpZATRAgkarQJB8L4qSVb8iPmichLvjyKBVDugP2dHYbXqvp4m\nLX2ocpOBzmtojwQ7JzRLIVBE5dj6MnRiWUZ2M1RKcy/UNklpEmp8sKFAemyxc7L6xRrBU9lo9b1T\njDEmvw3+fFkP/PbkRNw+SrxJ1znPiy/uGunxfRlJBlQ12nBeYR4mBRK8XPtXD+4AIDarNhBWHS7F\nle9slG3jJEWCaxvdB5yvtaDRxqFduruaKJZIpWSzpP3fbD/bagy+SD8bqHpNzXgt0GAEAAx4YSUm\nvLEups9/DRGrg2+W0eKaJ8Zjw+yJ0rVWZ3HApNdh/7wp2E2Vws1OcVWzUaZW5qZGrx95dZm8+tCs\nL3fhlWVHMOnNdeB5ARdqXYZ3u56bHOnmNQv6equ32MEy6qU6Ad9mhzd+sEUyXKVLiat9ZjWVKviH\nD7e6XfckaJFo1EvHbK8pEiQqmyqxv2I/OIGDnhXvVySQYHVYYdKL1wnLsMgwZUivtWS0QIJGq8Fb\nnjTpTElKgLLj1vthtkgUCZ6c5Wlov4WbR7pyw+lV1UCH0crgh70Z5nH0xF+Z3qFE+XcqB8KjX/0V\nvZ9bgRqz+o3ts02F0uP1x8sxcN4qzXU8BDg4Hl9sKZQZLcYLOpbBE1N6o3NWEoZ0zgDgWrnxdl3d\nMLwT7JyAX4+Wyba7vFE8v/fdm4eiX/u0mFMkKANzygEiLwhgFIaE9ED0QJEot+wSYFWGaGKgJklc\nEKlS8QTLMtCzTMCBBLXvJ5hUunNVZt87aUQVm4P3WfpRjfycFHTJTkKG08+EqFnSEgyylIXc1ASs\nePQSTO6biyev6CM7Bn1tHiyuRY9nluFsZfjPmZ2FVSipEwMFM8fmSds/3FCAU+WNsDg4XOtcTQeA\nbJU0zFintsmOZKPeo/eFWiBhz1nXItWuM67H3gKCvCBg2UHvJuBkHJls1En3xA6aIkHip1M/AQDS\njelugQQLZ0GizvVdGViDZLzYktECCRqtAk9miwQysSf12pVBf38UCeuPl0n7+oJI+edd3Q83XdRZ\n2k7ng/sj6Vby3/vH4E/jugFonnmX2SkR/P0I37XllYEGejWMHtDu9KDK6EBFuQ84cyA/23RadV8N\n/xAEAf1eWIm5iw/hqf/uj3ZzgoIMeom7tLfrqq1Tdqusje2PIgEQV99ibUW2ssHzyhIgBgqVA8zN\npyqlx/ud11Sg5R2jQds0E9IS9DK5/kvXDIhiiyKLUa9uFuoNtew1f3wW1h4rc3NsB1wlJDVil+YG\nEgjTBrTHH8fk4S9Te3vcp0+7NHx850WYMbgDlvx5nLSdvja/3XEWDl7AikMXIAhCs8Yq/kKfl2pq\njEZqzHRF/3Zha0c4qWmyI8mDPwIAtxK+DAP8tO+86r600hMQK2MROF7wWd2CKFGSjK4AU9s0TZFA\nsDjEoNackXNgYMUxCgkWWBwWKbUB0AIJGhotCl+pDX3biykFGUmitE/pfq1nWZ8T8+edBjj+lG0k\nzsNJJr2slBOtSFDKtP1heNdMKc88mEDCHaPzfO6bmyq/uTz/40FpIkc7KzfZOaw9Voa3VslvYL3a\nit+5UcdKq61rj5UHZdrY2rE6eGlCQgZgD0/qiW/uGRXNZjULks9b4pSteqtiQtyulYEEgi9pqL/l\nXSOJ2mSvktpmdXBuubN0iTYSSIgHRcKmpy7D7ucvl1XoyImilDrSGPVs4B4JKv2kr2CYg+Mx89Md\nuOUjl3cPWZH+1/pTqo74GrGDjQsukGDUs5g3o7/f1xadakmfWUSdUG22Y8XBEgx4YSUOnXc3QQwF\nJLVt6cPjUGN2n5Q12Tgpveu137mb9cYDdU5Fgj/869ZhyEkx4YstZ/DpptOwOXjoWQb3T8h329fO\n8ZL3gZ5lcEBhVPl/fxiCyX1z8dK1rqCtpEigAhsJQfhytDQsnAUG1oCcpBxJkSAFEjgLTDrXtWXQ\naYEEDY0WwbkqM1YdLsXRknqP+zxzZV/8MGu0VJJn48kK2ev+KBIIDVaHz5v9Jufxk416mRz5Hqqm\nOp33FwjkJv/f3cUBl0UipkX+1IxWmq2tPFSKf607he92npMFRCx2DjM/3YF3fj0p27/RxqFbm2S0\nz0hAMRU0ibUJXTyhlhpy36XdMTo/OwqtCQ5SKYQEEryZBhp0DFjG3fCUTLZ8aYT0LBNzVRvKnUGD\nnrkp0ja6X/pxT7FbcDQzySjbN9Wkl3kQxCp6HQu9jpVVh/EnRayl4Kl8qTfUUht8pYOQ1+lVXjJh\n2HWmGpe+vjagNmhEFlszPRKai17HSt40b/1yHM/9eAAAcK5KvF+fqWzEL0dKAbhUhaHEYuew5VQl\ndCyDfu3TYFfpo4+V1oMXRA+HDKr/iydqzD4UCc6Ovk+7VEwb2B5JRh04XsCLPx/GM/87AAcvoK1K\ncIgEXkx6FiPyMmULZDuenYxrhnTEx3deJBsnkuA0rUiIhdLRkcLO21HSWOLxdRtnQ4JOXERzS21Q\nUSRoHgkaGi2A/X7c4Ex6HUbkZUkD2Ycm9pC9rtcFtmLZxmnaeGmvHLfXTpTWY84i8YacbNLBqHPd\nQJ6Y0huFr12JDukJmH9Nf78/j4YMNF5achh/+X5fQO81S4EE39HxtET3ff5vzQk8+cN+HKOCNnQA\nh1ZJNNkcSDTo3AISweT5tnZeW37UbZs/QaFYhBh/rTosDlS9DWUYhkGCQdfs1AYdy8h8S2KB8nox\nkPDJnRfhyStEKfIZKie52mx3S/d4RVE+kzZfjAdmjsmTHreW8o+A+Ld+u+Mclu73nr9Mo1a1gfNx\nDpN5GP1WOtZc6cWoTSP62Bw8TPrI9uf0GObLrWfx2abTWO0MHtSY7Vi0uxiAb0+l5vDmqmNYe6wc\nHC+AYeSLOf++bTgAoKBcDIp1zY595ZUnappsXhUJySY93rtlKL64WwzqJFDlvX/YVQQA6J6Tglnj\n89E9JxmJBh2mD2wnqdr+fuNgWX/625MTZaoUesxF0qOS43TcECzzNs/D5T9cLqUwKLFyVhh14thE\nmdpg5axI1Cs8EjhNkaChEfcEEkztnCV2AspSR3qWQVF1EzYrlAo0pOKDUcdKMkC11YNySp6cbNKr\n1g7e/PQkv9IL1DDoXX/wj3vV8+g8YXYqCRL9uImkJ3pe6TxBrXh9stHle1CnKHmUbNK55d99sKFA\nS29oJlYVaX+8riaY9DrZOWb2UeJLLNEqP29u/XgbAPU+4KeHxmLZw5cAENORYs0jgQwCc1JNeGBC\nDxj1rNt3oEzZaJNiwoF5U6TnnsqJxSqZyUbpN/eWytLSICkFcxcf9Ps9auerL0WCWllgtRQJjdjE\n6uCCSm0IlkSDDvN+Piw9p9OvwnG1KscvpL97+6bB0niLTHwfuqxnGFoQGWrNdp999VWDOkjppGrj\ns0t6tsGcaX3w6xMT0CUrCRwvYLfTkHFAhzRZhS1lCVF6gee8s8wwGQO3TWs9KWYAsLJwJQB4VBKY\nHWYpWED+b3I0Sf/LUhs0jwQNjZZBIDe4eTP644Pbh6N/h3TZdiKrvsU5MVHC84KU588JgjTIU5NL\n0+O2JKNOuiFeP6xjAC31jEEleNFk43DPFzt9uiyT1IZEg+9AQpoXyXSJh7QMcjOz2DmY7RySjHo3\no6Z31pyQlaHU8B97jE2Gg6U9FdBTmwTR1DbZ8dnmQqw+XIplBy7g+53npHNLrWLLoE4Z6NchDUBs\neiSsOiSu+pFBY5JRB7PNIZP8q00qaDWRr/rjsQhZOfOWytLSMDpXmQNZ1VU7Xcl957aPt+H7nefc\n36NyCXG8gOuHdkT79ARc0rON35+vEXmsQZotBkuTIlB9vNS1YNCcKlG+IKoswtPT+mBq/7aY2DtX\nUtoR+b4hjgOPdRZHQMpBNc8fesGAZRlwPLD3bA2yk43o1iYZB4vrpNeVqpZrhrjGnkSZR7x1+rRL\n87td8Yidt8sWrqyceM5xgvrCRaOtESlGMd2QpDEQ9YIytaHB3oBN5zehtLE0LG2PFVrPnVqj1RLI\nWDrJqMdUFedfX/m6NVS0l+MFKRdt7TH3nHV6BSgn1QSGYXDwxal4/XeD/G+oF9QCCRtOlOOXw6WY\nv+SwyjtcbC+sAqA+QVGSnuQ5kLD84AXoWQZT+7eVba9tsmPzqQr0eX4F9p2rQUqCXlIp9KBywWNt\nUhcP7DpT7TbwinfotJix+f5Ncv70xU488NVuzP6Bqlrhq2oDy3g0aowWeym3bQBIMuhQbbbLrg21\n2u60hDWcburhgjS/NXkktEsntcf9f48ns0WeF7DxZIX8/HeiDMaV1VlQ22RHWqIBnbOSmmXQqxE5\ngjVbDCf0indzmf39Pjzw1S637Y9N7gUAyE1LwAe3j0BGklEKsNY0iQs4kfSOCAf+mi0C8nKPauhY\nYPWRUvxypBTpSQYwDIOJvV0pKsqFIrqyT7c2yQCA7jni/2lelKfxTpOjCcMWDMO/9v3L7TVPgYQG\newOSDeJ3o1QkWDmr5J8AAAW1YgWNb45+E9J2xxrxfeVpaEQIenCulpuqXPlTRu5p6Hw0IlVLMemh\nD9GNkL6hpjrlcsTQ0erw3K6TZQ347YTn1A0lKSo3vh3PTgYAlNZZcWmvHNw/Qe41Udtkl6kNspON\nkoR5SOcMabvZFn8ToGjz2wlX0IpI9sfEocmiJ4LJwfX1zu45yThZ1qB6bUcaT2k9CUYdyuvlSp9r\nh6qrmDKdQb74DCQQRULrCSR0zhQH8mrKGU9Yncaid43thtOvTsfwrpngeAENXvpOOvVh77kajHxl\nDQDxu26O4aNGZLE5eJhiZMI8sXcO8nOSMbF3DrrnJGPFQf/9PTzx/a4iLDvgbnT3yGT3tAWygk8W\nImI1wOIv3swWPZHqIR2CjEdrzHZpPPjpzJHS62rf1alXpmPpw+Nw1aD2AIAeuan4923D8HILLsO7\n+sxqAMDCYwvdXuN4D4oEeyNSDOKiV5Je7LebHE3geA6cwEm+CTS5SbmhanJMEt9XnoaGH9hCILmj\nZXNLDrjfMMnqUJ6K4c+aI6VSCSMA2H5aXPVfcPdIt31DAb2yanEGDs5Wmd1eo/nlcCkmv7U+oM+h\nJ3bPX9UPL1zdD6mUuVuvtqkyaTogBhLowWpmklEql0nPG3zlw2t4p1+HNJx6ZTq+vPviaDclJvDl\nE9ExIxEOXkC1Obpmc5tPVqDb08twvLQeepbBfZe6qrgkGXXYWlAl23/aAPW66d/cK5b7bIrD64gE\nElqTIoEYzqqV/PQECVaPyMsEwzDO9BwetSol8gi0IGHx3mLpsY5lYNAxYZGna4QOW5RTG2juHtcd\na56YgE9njsSEXrmySiCBcLSkDuP/vhb7i+QKLF8+SSSFq1pKbYiN76W5BKJIIOQ7VZzXDukg206b\nMfr7vehYBv07pMvulVcMaO9VeRrvFNWLRpXtk9u7vaamSBAEAUeqjkj+CXRqg0MQtxl07t8Xne7Q\nEonvK09Dww/UDOgChc7XrVZxtiaBhO45KW6v3f35TvzN6aZfZ7Hjgw2i3CkvOznodqnRs61Y+3ls\nj2zYOQE2B4+5iw8BUJcffr3tLO75Yqf0XFmxwhv/+eMIrH58PO4e1w0zx3ZDgkEnBV2yk41uBkJm\nGyeTz2anGDHe6Qrdlfo+tHrmgUMGD33bu/L+w+GkHUlCNWj2ZSiX4vT7iHYAi1SoWHu0DA5ekPkd\nJBlcj/u0S0V+TjI6Zao7lTdnUBorkOBnUpwZRQZDlrNCSSApXZIxrvO61zEMeN7Vx6tdO3RqQxmV\nBsUyDAw6VtY3Ozgery4/gsKKxgD+Eo1wUWexo6zeKlVMiAYf3TECI/OyMCY/G0O7uBSEJgOLRhuH\nw+frvLxbnQ3Hy3Gm0owZ722Stjk4Hm+sOub1fUSRsOtMNXQsgw6K6k+xzge3D8cVVBptIIqER50K\njXdvHoorB7bHq9fL02JpvwWS+kHIbMGBgUCoslThn/v+KT0GIKuwoBZIWF8kLrYRA0WWYWHSmdDk\naJKCC7Qi4ba+twFwpT60VLRAgkaLxxoCuSa9Oqbmlk02eapkQCYo9GpRuMry9chNwelXp2Nib1FO\nRa9KqklXn/nfAdnzUd39l8Nf1qetzNuAfn9mshFJily8Jhsna0NWshEzx+Zh85zLJHMfIPoTuniE\nnKPfOlejWwLv3zIsJMc5VOy9BKxRSv2JDWm3VIKLGlzSTt33T8jHmicmeJT/x1u1Bpr+TgPMnJTW\n4xau7Cf9gSgSSABRLFHMS1WB1AxzaUUCXUFHx4rXgI0KJOw+W4MP1hfgyf+6ey1oRJ7XV4iLERUN\n0VNNXd6vLb6bNRpf3zNK1seQxYDNp/xPjSQUlLsHqqrNdry/9hQAz2Ud6ZX2bm2SvVaRikWm9m+H\n1290BQACCf4+OrkXCl+7Ep2zkvD+rcPcqjjQAehzVa5J7JH5V2DL05OCaHXLYcmpJdLjcnM5eIFH\nRZPr/L1/9f2S8SJh64WtAIC3JrwlbUvUJ8LsMEtBCD3r+u4fG/4YpnSdgs6pncPyN8QKWiBBo8UT\nirxPnY9AApHhebqZEW8Cuk53UhhXDRmGkW70Zrtrdd+fCXqwuckkQGLUs2BZRhaEabK7BxIYRlxN\noL9Xokh4c9WxgGqrt1aKa5rw8tIjAES/jZbC5L65ARnQecLXSq/RqaKJdo44WTEm5z9tdGWiVph9\nXaPkGuwSh7XV/3XbcPz00NiYkXBHgukDRWltIFUTSICY/NYGHQurg8fMT3fIttPQioQLVGUdlhE9\nEmhFAlE8kFQ8jejy5dazAIB/3xaa4GooGZmXhRSTHi8vPeI1tUaNDcfdDakrGqzSwsLL1/rO0Q9X\nmmi4oYMHoVxY8lTBItGok6U9tGZolYBDcOD1Ha9LygQAOF17GvvK9sneU2OtQaeUTkg3uaq6JeoT\n0eRoklQKtCLBqDPizQlv4tJOl4brz4gJWs+dWqPVQlb3Fj84ttnHoCfDpLIBDZmn0B4BsjY4jbHO\nVLqi76YwD5TJjanR6goe+KOczWsT3OTj8n6iXG9QR7GzpevBW+2cbNUrM8koPaYne19sOQMAePfX\nk3jw691Btac1cIaSH7ckkzqGYXD0pWk4Mv8Kn/vSihYlvsqZkklrtF3rSTCNmCTSgUl6ADi4Uwa8\nkWDQ4f1bhuGrP8WfR0ZaggGDfPx9LY3ctASkJuiRr5Ia5wmiSCCrkTkpJlm6glpAkU7xoXPaKxqs\nYmqDw/W6xR4b6pzm8PqKo3j02z3RbkbIOHTepaiKxWuDZRncNa4bAGBLgW9VQoPVgT99vgPl9VaU\n1FkwpZ+8utPRkjqwDDBjcAdc0jPHw1FctE+Pr7QGAn2vDuUCAF0ectb4/JAdtyVBUhdu7XsrAOCr\nI1/h7V1vy/bZVrINvMBj0veT8L8T/0NRfZGbceKFxgv46dRP+MPSPwCAqtliS0cLJGi0eIgaYGDH\ndB97eoauqPDL4VK3vFEB4gCMnhjL2yAOyugVz3Dnr5PJU5ONw9WDRTOeCb3db8o3Du8kPV756KVB\n35R/N6wjDr04FXnOMkL0gPSdX0/KvgN6xZWeCB4orkWlwnjMzvEoqZW71muImAwttys36lk36aYa\nG56c6PG1P47N8/4ZOvH4thgOJBDD1k6ZibJyXZ64clB7tE1r2SZPLQkdy+BEWT3y5izFrjO+VQBE\nXUb6+TapRpl/j9o140mZk5ZogEHPyM7/WCuHGgj/XHcKP+49j11nqlETZQPVUPDFZjGwPqlPbsx6\nAcxwjjH8SQ+76YMtWH2kDPcu2AlecE9fOFNphp0TZIsQanxzzyiseWJ88xsdQ4TSE4YYJr50TX/M\nmdYnZMdtSXACBwYMnhjxhLRtW8k22T4HKw7ii0NfoMxchrmb5+JQxSH0ze6rerwycxkAl39Ca6Ll\njj41NJxYHTwMuuCM55QO4sqyamR8lmLS4+eHxrm9nxjeqKVFhAsptcHmkNr/w64it9KK9OCyfUbw\nEw86rUINUkHioztGSG7lADCyWxZWPeaSgK045CoDJQgC7v9yN0a9uiai32G8YI3j1cNQ4qncpUnv\nPRBhiHJqgyAIePy7vdhRKNYHb7C4BxLWHRMlwGpmrxrxj45hsOlkJQBgzZEyn/tbFIqEjESjrC9X\nU7wp+86hXTLwzs1D8djkXk5Fguv8r7fE/4D4d//ajGve3xQTZV2DgaREvv2HIVH5/Fsu7oJ3bx7q\ndR+igPxhV5HX/X7/7y045DRlJGaxuakJeP6qftI+ZyrNKK5pwqFi7+aNo/OzA1LxxDLJIUxtIMPV\neK9kEU54gYeO1cHAGrD55s14f9L7bvtsPr8Zb+56U3ruEBzok+U9MKNm0tjS0c4yjRaPzcH7nEj4\nQikXV+aZkYEKwwCZye7SpuJqMR/L7txv/ewJQbXHH8gA02zjJFUGAFTU27D5VAWKa5xtcq5CXdKz\nDdISQi/L+vD24XjhatcgYUtBJbKTjbhcIWcExJKRWcmiquPZ/x10bX9uueRWHW35eSxidX4nr1w3\nMMotiS6f3HmR27YfZo32+T6S2hAtRUKdxYFFu4tx2ql0IuoDOpDwxOW9ALj6EI2WBe2foyybq4ZZ\n4ZGgLNOmVqiEV5zeBpbFjMEdkGDQwaTXSRUzAKCcSpNwxHGfe6bSjO7PLMMDX+0K+2dVN9pQWhd6\n1dyh87W4dkiHsNyf/eGV6wZKqkZPkLTO305U4KAXc1s6NdTmIIahrMwT5X97xNKkx0rrm93meCOU\n6jGS2qDdKTzDCRx0jNh3phpTcXF7MQ2wR0YPzBk5B6mGVNX3KQMJjw9/XPa8V2avMLQ2ttECCRot\nHquDC9qPwF3MIO+iyaCNZRikqtzsyUon5xyQRWJAkEQHEqgVa4uDwy0fbcO4v/0KAHBwAnq1TcGC\nu8OTTz2lfzvMHNtNel5jtns1Uvvv/WPcttH1zbVAgjvk/BrUqfnpOy0BpZw7PdGAEXlZPt9HVm6i\npUhQBiqrnJNKOpAwwPnbRtsQUiP80P2dJ4jZYoIzSK5Mq+NUIgkORSSBlo6nJuhh5wRJ6dBIV/uJ\n4z6XTHCXHSjxsWfz2VFYheOl9Rj60i+4+JU1IT22IAgorbN4LPUaK6QmGPCXKeIk6qp3N3rcj05j\n2HdODDiY9DromJbj7RMIvdqKiopQpqwQL5QWZJcUcjieA8u4xqEmnQlbbt6C/0z9D27te6ss5YEm\nP13uOUF7Iiy8aiGGtx0engbHMFogwQfP/O8AtpyqjHYzNILAaueDdgAnDtdkpUg5riIdN8MAqSqy\nfhvHw+bgMe/nwwAAnY/cv1BAHIHNNodq7qsgAL//YAscPA89G/6u4PHLXZFab79Hso96yv4Mslsb\nZHKZ0IK9EppDnZ/ybBJojGZqA0212Q49y8icvNM8GLlqtAz6tU+THjf54U/QZOeQYGCllL0MhSJB\nvUyxfBvt/UMm3PXOtBpahdBv7kp8saXQZ5tiEfL3hJMb/70FU97eEJZjm20ceMGzkXMsMdpDatna\nY2UY//e1KK5pwplKs7S9xKneMBlYTO3fFt1zkmXvUz5viXz1p1FY8udxITVJJostkRjXxSu8wEuK\nBEKKMQWZCZkAgCu7Xyl77YPLP8Djwx+HQSfvZ+lgRJfULmFqbWyjnWVeEAQBX287i5s/2hrtpmgE\ngZ3jg84VI7WbR3UXb5TKQRp5xjKiF8Or1w/Ekj+7vBLsnCDJlgFRUhpuiOqhtM6C3064nJRJfiIg\nlvayc4LHckGh5OFJPaXH9GBCSarJ1VHPUJFTaooEd4jBFTEN1BBRk3erEe2qDco5X1WjDemJBsk0\nCwBSTPHpBu3gHThQfiDazYh56Go5dU12DHxhJRZsKfS4f5ONk1UjyfQjkOBQBGEN1OSFqF9qm8Tg\nm02x72ebPLcl1lCbk7VNM0W+ISGgwmk6nOahtHQsoaPGNXRw9KWfD+NMpRlL959XfZ9Jr0N2igm/\nPjFB2ja5by6+v893Wlq8k5NqwoAgjMDVGJMvlpHt015dnq/hTG1gPY+XEvQJ2HCTKzg4psMYzBww\n020/OhihDDK0FrRAghc0U7eWgZ337f7ri9lTe2PW+HypTJFyZYdWJADAzSO7oH+HNNk+RdWuyXMk\nSvSlJeqRlqDHG6uOy7Y/vUg+qN9+ukq2MhVt6FX1qf3bub2uBRLcISvpLbl6QziJdmqDWjKrcgUy\nJQ5WJNX4cP+HuGXZLdhUvAnbL2yPdnNiFiPVB5fUWVBvdeD5xYewdP8FHChyzzk32zgkUXXolRNN\ntfGLMt2Bvg8Rb5pqZ5UDpS9CPCnP1e6vuamRqWDSwQ9/C3/geAE8L2D839cBEM2IYx2OSp0hASnA\n1XcVlDe6vQdQv2+9ct1AZKfEZ/An2tw4ohO2PzsJ/Tu07lRHb3A856ZIUELUCaPbew5o0cEIPROf\n9+hg0UadXqAdkOPZbKi14+D4oBUA7dITMGdaH2nl8lyVGSsOyqsKAPL6vQzDYMmfx+Hhy3oAAA5S\nDsTKKhDhgGEYyZDLG012LiLt8Rd6FbZNins5TS21wR1iWmWMoYBQtJgzrQ8endwTaQl63HKxf1LD\naJstKgOTAFCoUO3Eg7RZiSAIOFR5CAAwa/Us3L3qbrc0Dg0RWjVXVucyOnzw6924+j33nHOLM7WB\nQAcVAA+pDYrTe9XhUukx8VioarRh/s+H8b3Cff9UeSP+sfp4XJSFZFWiHtH0FjlYXIsr/rHB70oY\nZfUWDH5xFW77xFWOrnub2Jf5D+2cid5txVVwouIExGpWAPDtjnMA3Etxq3lY5Wqla5sNwzARC5zF\nIxuLN+K749+hyuK7zO76m9bjncve8fg6HYzwpnBoyWijTi/QN+LCSvVIqkbs4/CjHrHecevsAAAg\nAElEQVS/kHzU+7/ajVlf7sL201UY8fIvUvRdOYAZ0DEdOaliVP3t1cfdjhNufE0+yMQzFssE9Wqb\noirn/Oi3gii0JjjOVpqRN2cp9pytDsvxpdSGIL1AWgKzxufj0cm9sH/eVPz12gF+vccYbY8EP/ZJ\nNsZfIOFPq/6EDUXy3HELF3pX+5aAgbp26dVcNfrPXYGlBy7IggeJikpCSvXBjsIqvPXLMQDqpeYk\nRUKjDf/ZdFr1c/+x+gTe/uW46muxwtGSOqk/nD6wnXQP9Md3ojkoF5kcKgGcv688hqMl9dhR6Hvi\nAgBF1U1osDqw2enPNX1gO1mAPVZhWQazp/YGAFmZaeX44qM7RuA/fxwhPU+Pg7QNjZbDL2d+8Xvf\nrIQsJOg9B2Voj4TWivYNeIG+IdQ2hd+wRyM8iKkNoTnVlYGC+UsOoaLBJrkPq8UHlJO7Qy9ODUlb\n/OEiL471qSY9cp15o5HwSAiE3c9fjh8fHKsaSPh629kotCg4fj0qrvwtdK7IhBoptUELJMjwd/BN\nAmqxpEhQQuTaNwzvFO7mBM2xqmN45rdnsL3EPZXBbPfsj9KaOUx51/gyCSUVFeh7i45lZM95xYT2\nxn9vwe6zNQCALKfS69npfaXXiSJhziLvfhYfbCjAakrJEGvc+4WrzOOr1w3CgXlTkWTU4WyV2W/z\n1UCwUMHHkd2y3K7lwopGrD9eDsDdpNkTTQol4fheOcE1MoIkOc2SG62uv0H5vacm6NEly6Ww6NXW\nlcu/8amJ2PHs5DC3UqM1U2YuAwAYWXfFa6AQFUJWQuynHoULn6NOhmE6MwyzlmGYwwzDHGIY5hHn\n9iyGYX5hGOaE8//M8Dc3stA34jofKwQasYuY2hCaibKyRFF1o3hekM1q8xaT3rX6wzJAskpVh3Dx\nyvUDMf+a/qqv3Xtpd2kVK1IeCZf6OSDKSjYiyaiXOdWrpTnEC2Tl8Nsd53CyLPS1sW0cD5aJ3O/Y\n0jBG2SNBLY6gNM8DgJN/nYbXfzcoAi0KjsfWPYafC36Wns8eMVt6fKrmVDSaFPPQ6WX+jjd2nZEr\nnOhAotrKOCErWQwg014CytKpgGdF2+ELdarbY4FKpzmhUc8i3XkNkRS/8zVNIf88Mul/6Zr+6NMu\n1e17f+Cr3dJjTplb4uOYBF0cue+TgFR5gys9p8bsOp//cFFnJJv0SEt0nVu0YqFTZpKk4tTQCAfl\n5nL0zOyJhVctDPpYJLWhY0rHoI8Vr/jTOzkAPCEIQj8AowA8yDBMPwBzAKwRBKEngDXO5y0K+oZQ\n02TzsqdGLBPa1Ab5cyKXJEdXWwGlV4kiLT1vk2LCTRd1BgDcPyEf867uJ70mlg8TO8FIKRK+uGsk\nXr9hED6+Y4TvnSGXc9MBmXhDoMTr3mpsNxerI/gSp60ZlmWgZ5moGXmq+QaMUFET6XVsxNKiALHi\nwuHKw9hRsiOg952rdylv/jrur7ij/x14YPADAIDihuKQtrGlQBvO1VvdFZD+eEvQEzKlImFwJ1de\neq5zotao8jk0Iz0o2jKTYz+oO3+GK4D+kjPFqd7iCLnfFfGMSDDooGMZ1JjtOFdldntdfOzfZ5sV\naRjbT8dPCfK8bFFpQMylz9c0ySpWDesqrjlmJRkxomsm/n3bsMg3UqPVwvEcjlUfQ/f07uiR2SPo\n49k4cW6oBRK8IAjCBUEQdjsf1wM4AqAjgGsAfO7c7XMA14arkdGCkykStNSGeMXOB1/+kaBUJJCV\ngyMXxFVmNZMn2gAvGmZ4Jr0Oh16citlTeqMrZdh044jOLkVCBFc8fj+iMyY7q1/4gmUZScodDyZf\nnqANIv0dTAbChxsKwnLc1oSDF7DsQInvHcMAPeVb9vAl+PsNg/DuzUOj0haaRScW4aYlN+GulXfh\n6yNfY+uFrZi9fjZ4wfO59vqO1wEAyYZkfDTlI8zInwEA+OOAPwIA5m6eCzunKfyUJFCBUrWYAelD\n6ACB0heBVtTQHgl1FjuOlzZIz4c7J3M1PpQPZNKnxBqjfTHHC2i0cXhkUk/8YaTLaJUEUd779SR6\nPLsc5fVWT4cIGFJOOdGok8YHl7y+VnqdDvDS5scnSus93tMsCkXCvZfmh6y94SbRqINRz0o+H+/+\nekL2en6OOAbR61j8cP8YXDGgfcTbqNF6WV+0HgCgZ0OjDCZpEu2TW+95HNDsgWGYPABDAWwD0FYQ\nhAvOl0oAqM4MGIa5l2GYnQzD7CwvLw+iqZGHvhFH0/FXIzgcnBCyqgTKslJEkbBwp7gCp/YxnbNc\n9cGjtWqcbNKDZRlpsDq8aya6tUlGgpGkNsSWRwLNq9cPBAA8PKkn7h7XTdUoLNYJV9WXFxYfRN6c\npWE5tj9su7ANM1fMhINvGYFWeuUsktATxwQDixtHdJbUQtFkZ8lO6fGr21/FPavuwYrCFaix1qju\nX9lUiQWHFwAAPrr8I4xqP0p6LUHnMqyqs8WuND5a+CrdSvw7aKWkMh1BFkig9pu1YJd0r7pvfHdk\nOeXnSlPHD24fLnvuKbXBGqPjIZLqQUpYEjISxb+XeBWE0jx71peiJ0OCXgedyn2U/g6JAWGD1YHL\n396AJ77fp3pMpTFkp8zEUDU3IqQl6FFvEf/WnYXVCjWMVk1AIzp8deQrPLL2EQDAsxc/G5Jjknsh\nKRXZGvF7VsMwTAqA/wJ4VBAE2ShAEDV3qro7QRA+FARhhCAII3Jy4scwBgA4ahXR7mdum0bsYef4\nkOWOq9WnplHzSOjdzmUkFO3yfCSFgRhCJTgDG8GWxwwnBh2LwteuxJ1j8sDAP4f7WMNbvnIwfL7l\nTFiO6y9PbngSO0t3epxYxhMsA+RlJ/neMQzQBm2xVEHlZO1J1e0Ntga3bRaHBe/vfV96PjBnoOx1\nOu2LE2JzRTua+Erdsjsn75w3RQInDyRwvIBPN52W3P/7tEvF09P6YlT3bABiNQCaqf1dz7tmJ2Ha\ngPa4pGcbt7bEaiCBeCBc1idXtj1d4Tdy84dbQ/7ZRj0rU5UAYgD5fI0FbVKMYBixJOIH609hzRHR\nrHLp/guy6gYEZdnmeDPR1bGMpJyparRhAFXu0VfATEMjXLy2/TUAQF5aHlKNqT729o/b+t6GwTmD\ncU2Pa0JyvHjEryuaYRgDxCDCV4IgLHJuLmUYpr3z9fYAysLTxOjhoIIHDq12fdzi4IWQeQD4Mkr0\nlCLw6OSeAKC6YhFJiPy9nbNGc2IcKBJoWJZRlf3GOspAgjJ/mecFXPPeRjz49W74i9UhH2zSqz7h\nZEPRBgz8fCBqrbWw8+KKpqf87flb5uONHW9EpF3BMqp7dtRMvsi3d0nPNjIFUzThBR4ljeqpHvU2\nd8PQv+/4O74//j0AYN3v13k9NjlvNFz4Us3ZJUWCa1yiZpBI4HgBOwqr8OLPh6VtRErfJTsJha9d\nicv6eE4xW/eXCchJNeGftw7DdUPl+b/KvidWOFFWD5ZxT8lIVdy3QxXYpYM6ZpsDXRTX7s/7z6O4\npgl3j+uOjhmJKKltwqvLj+KRb/dK+xwoqnU7Lq1IuLhbVlyUfqRhGUb6buosdqQmuAI58ex1pBHf\n5CaKAcbPp33uY0//aZ/SHl9O/1Kr2uANRuzBPgFwRBCEt6iXfgJwp/PxnQAWh7550aVtWoJkChcu\nabJG+HFwfMhcj30FEjylLpDtDKI7IBjVPQsPTMjHX68TVwvJSkcsrYJ6g4F/pfJiDWX/sa9IvoL/\n5H/3Y19RLZbuvwB/mfr2Btlz5WA/HGy/sB0PrnkQAPDcpuekCaWNl0uJ95btxd6yvfj++Pf4/HDo\nbtrhRMcyYVOO+IIElq4e3CEqn6/GieoTsoDBw0MfxgNDRMPEers8kCAIAr47/p30PDsxW/WYc0fP\nBYAWkwoTSnwFc4nawJsigdC/Qxo4XkBlg/y6VK50e4NMXlMTDHj7piGy16wx6sfy69FyXNwtG2kJ\ncgVCuAxKK5yVCVJMekzsk4suCkXTYwvF1IVhXTLQPj0BF2otbsegy0cKgoAas03mndCzbUo4mh5W\nWIYBL4h/j50TZOOiBE2RoBEFqi3VKGsqw8z+M1v1pD8c+HNFjwVwO4DLGIbZ6/w3HcBrAC5nGOYE\ngMnO5y2KZJMek/u1hT6KA0yN4LFzQsjKP6b4CCR4kiBGO6WBoNexePKKPshyum6TAEuoPCTCDhOf\nqQ12haLpfI18QLnlVOCu3IWVZtnzlAT3coGh5u5Vd0uP151bJz0mzsUA8L8T/8Pty2/H7ctvD3t7\nQgktx40WamatkUAQBKw4vQIWh+u8fGC1GDR4dNijAICr86/GZZ0vA+Ce2rD1gksqvv3W7R4/h8hJ\nNbNFd3z99qQPcfgRSEhLMIATBJnPE+CfYe2TV/RGeqL3viTWUht2n61G3pylOHKhDt1ykn2/AeJK\nebCQVIq3bxoCk16HPu3U5dIOXkC79ET1QAL1m2w4UYEh83/Bot1FMOlZPDSxB568ok/Q7Yw0LCv2\nKSToRY8vYmUspNF6sHN2XLrwUgDA+cbzUW5Ny8Ofqg0bBUFgBEEYJAjCEOe/ZYIgVAqCMEkQhJ6C\nIEwWBKEqEg2OBnqdFkiIZzg+dOUffRn9+VIkxBok5SNUHhLhhonTSIKyfvnCnedwvNS1qjuht+gf\n072Nf4NgQDS0AsTJxG2juuCKAe18vCN80FL1uZvnyl5LN0Um5SJYdEwUFQnOCV+0wnlbLmzB7A2z\n8Yclf5AqMpQ1idmKN/S6Afvv2I92ye2QpBdXXM0OeRCLlIdkGRaJes/GcKxzyFFijk51jFjGl/+O\nXUWRkODhfpSeaADPA5zC2ynPj/7lgQk9sO+FKV73iZXUBkEQcLC4FuuPuYy8/TXjLSgP3nBx22lx\n2NszV1QN0BL+BqsDY3uIypwhnTOQm2pSrRZBBxIKnWavFQ02tEkx4S9Te7upK+IBUZEg4N1fRY8V\nevwVb2kaGvEPSbkDRGWdRmiJj9lDlDGwbNTqi2sEj4MPndkifRw1GbJy5ZnQ4KzX3SYltupvk8Fr\nqDwkwg3DAIKHSIIgCHhz1TEcuSB3hP9k42k8/M2eSDTPI+uOyyvWbDhejilUagKpFhDISp8gADPH\n5uHw/Kl4+dqBPtUywWLlPJdM87bCbGDjYyCsYxnZJC2SkIXjaI2xixuKAQCnak/hx5M/yl5L0idJ\ng3+DTvwt6dSEFza/gI8OfAQA+ObKb7x+DlEukBKRGi58KRJIRQZ64pnkSZGQqBcVCc7u5JKebfDS\ntQPwnz9e1Oz2ZTgNC1kmdhQJ/1x3Cle9uxErDroCU0lG9X7wp4fGyp7X+Sh96Q8/7inGRXmZqgGa\nmZ9uR6+2qUhN0CPZpEd2itGtGgMgTxOh+580H6qQWIZlGHAC8H9rxNKPepZB1+wkTFKYYGpohIrF\nJxdjReEKbL+wHQ7eATtnxyvbXsHhysP49eyv0n5d0rp4OYpGc9ACCX6g1zGa2WKcYrFzqGiwhSWn\ns0uW+8pbhwz10kZ1TeLA+55Luoe8HcFABqWeynzFGgzUa6wDwJlKM9799SSe+u9+2faXlhzGT/ui\nJ2ezczzK6624bmhH/GlcN7fXOV6QXNVtAQQsm+wcEg26iK3wlDV69tMlHglqpouVTZVegxCxgl4X\nxUCC8/9opTbUWV3Bt3pbPSqbXKk2JHgAuGpv04GERScWSY/7Zffz+jnX97weADClq/cVbzUEQYCj\noiLg98ULyvSyjhny+8t25+o3HShVKt3IMdITDc6qDWJ/8rffDcLto7qiTUrzzUSJQS8vxE457L+v\nPAYAOEapuzzdy3or0g7+9PlO1f0CodpsQ/c2cg8DUq54R2E1OF6QgvWZSeqLCHRFMLqCw7PT+wbd\nvmjBMkBJrUuFp2NZrJ89EZ8EEcjSaH0sOLwA9/1yn1/7PrfpOcxePxt3r7obtyy9BTtKd+Cbo9/g\npiU3YVvJNgDA+5Pe93EUjeagBRL8QK9jZU7JGvEDkRJmh0EJcMPwzgDElczC165E4WtXeqyR/OfL\neuCNGwdHVX6uRlWjOAGMl9rOjJfMhkbnICwQQ7FI0OCspz2wYzqeu8p9okXXNLc6AzuldRb0fm45\nDha7O3oD4kDewQsec6RDzb7yfZi3ZZ7b9qdHPi22x+mRcNuy29z2ESDgTF10y1T6A+00Hmmk1IYo\nKRIqmlwT9GRDMnaV7gIAyVyRQNQlx6uPux2jc2pnn5/TMUU0BG1Oze2ahQtxYtwlsBx3/+yWwJ1j\n8tAzN0VSrQ3uLE8Jmr9ErL7w4NcuddUzisnmD/ePwR2ju0oSe5tzAcRX2oQ//Ou24bh+WEf075AW\nM4qErirlWk0e+sRwVAtotHJuBsxXDmovPeZ4QQrueDLsphepGp33rs/vGolxKmU34wWWYWTqi3hR\nPGrEDv/Y9Q+8vuN1bD6/2ee+tVb5OOlI1RFVY/PRHUaHrH0aLrRAgh/oWU2REK+QyeXQzhkhP3aW\nc4XBn8lHskmPG4Z3irn8wOpGUd6ZG6Wyd4HCgPFYapDE+qJtmKek3OnsTaTByhSEYyWu1TSiSFh/\nrBxWB4/7FuzC4BdXocYsd1/feUZcnWybFpkA0G3LbsP2EtFE79srv8Wu23bhwJ0HpBXoH47/gIMV\nB7G/Qq4GuWfgPQCA07WnI9LOYNCzjGROd+vHWzH2tV99vCN0uFIbIt8/FNQW4MsjX0rPzzecxxPr\nnwAA3NjrRtm+RJGw8NhCOHgHON41WfAn91RN0eAvDb9tBADYzsR+UKo5dM5Kwi+Pj5dUAyO6ujuL\n/29PETpnikqFt34/GO3S5df/kM4ZmH/NAGlyW+0MFIdC6dKtTTLe+v0QJBv1sMWIR8LgTu73dX+M\nlacNaIe8NsGVWeV5AY02B1JM8gAF7WnA8YL03d84Qj3QRqfNNtk4pCcaML5XTlBtizYsw8gC+qEI\nZGm0Lj45+In0mL7PqPHLmV/ctqmlz8VLmmW8oQUS/EAzW4xf6p2rwUkhzB9PNuqQkWRAWqJ4zAcn\n5ofs2JGmspEoNuIkkOBFkUBUQ7FWHvKMs7pCD6ch169/GS97nRgx3jG6K2wOHgeLa7Fw5zkAQHFN\nE2qb7NhzTl4u8paPRKleJ5X0mlCz5uwa2fNu6d1g1IlBNPL/isIVuHnpzdI+F7W7CL/d9BvuGRQ/\ngQSWChhvOlmJYoVBZjgRomi2uPz0ctlz4ncAAG0S5aui9EDsQuMFNNjF6g1PXfQUruh2hc/PIu9/\nY+cb2Fu2N7CGOq9vJkSlfGMVUorXqGfx5d0XY/GDrtz+xxbuw4whoqrj2iGey73mOysXkJSuUFbl\nMerZqKU2lL/7HupWrpKeq3kOeJu0rn78Uiz587iQlHo12zkIgnpJ6P4d0gCIyjHy3SdQSolNcy7D\ngXlieg9px8HiWny2ubBFrN6zLIMas8uDwtDCr1mN0EIMfwk/HP/B6/5VFnFhZWreVGnbyRrR6DPZ\nkIw5I+fg52t/DnErNQja1e0Hmtli/LKtQMz19VSWqTnsnns5tj0zCQwjpjTMnhp/5ZkIJKUh1kwg\nPeHJI8Fsc+BslThhV5Y8izak1jhZqcqicmUFQZCMODOTjOAF4Kp3N2LXmWrZMWZ+ukP12J0zg1tV\n88aGog0oqi/Co2sflW1PMrg+08iqnzevjHsFGQkZSNQnIjshGyWNoXPpN+/YgSN9+sJe6tmzoTno\nWSZqQahoeiScqxeDVvPHzJdSDwCgR0YPt32JogAAiuqLUGMVA1xppjS/Pot+v/K88okk24jcsGXh\n0YV4bO1jWH9ufcQ+MzPJAAhibv24nm0wuHMGZo13Bautdg4mPQvWy4R5fK8c5KaacLJMDPR42zdQ\njHo2IC+XQLAWFODokKGwFRWpvl7x/vsofuQR6Xllg9WtSoNahSTeYkHjtu3okZuKAR3TRfVRkIGE\nRme/rRZI+L1TfXC+tkn23W98aiLeu2UoOmYkSqkWJOXh5aVi6kpFgw3xDsu40iaB2K1apRGbkFQ7\ncg96edvL2FS8CWVm9Xt+nbUOifpEvDH+Dbw89mXZa6+MewW39r0Veel5YW1za0a7uv1AM1uMX3af\nrUHvtqkhlYCb9Lqw5FtGg/duGYqP7xgRN4oEtSTyc1Vm9Ju7Eo98K65wxpKdyZELdXh60QEAQIrT\nBIyu/HGirAGNVgcSDCwSfZQtU3NtV0qbQ8WZujN4cM2DmLZommz7gmkLZM+JIoFm3uh5aJfs8gJp\nm9xWqgoQCqq++hoA0LQreLM0mlCsUjaXaHoknK49jTEdxuC6ntchOyFbtl0Jy7BINYpBWbPdjFM1\npwAAXdO6+vVZOsZ1jldaKr3s6Y5A5K0RkknbeTte3vYyVp9djYd+fSginwkAf9nzLZYvno2Lu7lS\nG4j6DRDT9ZJ89BUMw8hc/0OpSEhL0MtWm0NJ7Y+LIVgsqFuy1Oe+9RY79hfVYiJVCeD3Izphan93\nH6KSl1/G2TvvhPW0eE7rWDboMR0xa1QzsBzQUQys7TlbI/vuO2Um4apBYrUnojwglZ62FrScCurK\ngChJ69PQ8AUv8Jj2X3HcQS9azFo9Cw+sfkD1PXW2Oum+NKnLJIxsN1J6bUS7EWFsrQagBRL8Qs9q\nZovxSqPVgXS1Mkp154GmavftrYzsFBMm92sb7Wb4TZrlAh7XfweBuh4rG+UrOMU1TSits3j0Uogk\nJ5wrgoDcTXzJn8cBAArKG9Bo45Bi0vusf17TJP6dJ0pdxzSEqKypkp0l6pP0npk9Zc/Vcg7pVWcA\nSDOmSWX/QgHjHJiH+vfVsUzU/DXInxKpVOJGe6OUWlDRVIG2SWIfMLnrZGkfT8GBr6Z/BQB4d8+7\nWHF6BQCgZ0ZP1X2VBOUB4fxtIpXaYLabZc/PN0Sm8othtfiddqNKChqp6/xkWQOykn0ryOgJbChz\n1NulJ6K0zhKWa4Uxin+XYPNd5aWwwgwHL2BMviv95vUbBstSCAi2UwUAAK5KnKzrWSaoMd3h83U4\n4DTCJSlrNAM7ZsCkZ2F18B7VIAzDOIOXLW9sqfybMzxUrNDQULLtwjapClROotwr5Fj1MdX7fp2t\nDmlGMXiXYkzBg0MelF4j2zXChxZI8AO9jpGixhrxhcXBw2RQOc3f6gv8Y3DkGxQhan/6CcfHXQKB\niw1TrFBx1bE5eFj/I4TSw9I2tXHaxa+swU0fbkWdxcfKWW0R4AhfaUI6jYFWsZA0h1WHS9FodSDZ\npMdAFeMwGiLFtTqNztqFUGVTa63FWzvfgp0Tv6+95fL89ceGP4YNN21AskFeL50uDShtUwQXcpPE\nFUOPJpkCjx+O/+B3ichzRN0Q4gG4jom+IiFSLgkPrH4Aty+/HVsvbEW9rV5azZk5YCZW/m4l3hj/\nBj6e8rHqexP1oi/HqdpTWF4o+ivQK0fNpcpS5T3gRH7vCKU20IqMLmUC1u74zu/3CjyPC3NfgOXI\nkWZ/vmB2BTJMlDR8a0EVTpU3qr1FBi0nD6UioUNGAuycIKVsBcJzPx7A49/J+5bfTpQjb85SfLjh\nFBiT2F/yVt/Hrnf27e3SfavpGIPYJwl28T06HYNGa/PvjdPf+U16rKYOMepZZDuDPd7Uiy3VyFt5\numVqigQNP9lXvg8AMLbDWDwy7BG319WMeulAAgBkmEJvrq7hGS2Q4AehyKfTiA5WO6e6QiG+qF5a\nryVQMu9FcBUV4Jss0W5KSNE7I9WCwONcldlZK1392tx+ugoLtnhxeOd54O3+wA93haOpAMTSh2ok\nO52+F+0uFgMJRr1kkKbkvvHdAbjKhM1dfAgA8NEdoZPsvb3rbXx66FOsOiMamRXUFshez0nMUS3Z\np5baoAwudEntAgDgBPWB+8bijXhxy4v4x65/+GxnaWMp9leKqSIhDySwbNT6eVfVhvB/VqO9EbvL\ndgMA7ll1D5ocTVIgAQA6pHTA1LypyElSd4436UKTBjWu4zjZ87tX3o17Vt3jpgQguFRIkfmNjlYd\nlR6/8QmHYfd/4Pd7HeXlqPnuO5y7178a6Gpwta77U3JVGS4/sz2g95PgQV52kiydKljap4uBpPO1\ngd9bvtx6Fot2y9Ocvt0uenS8suwoWJN4bglW7z4BZyvNuOVj0XA2NzUBd43thp8eGutxf5fSQTzu\n19vOosHqkMpDe8J+/jzq164FAJTVW/DQ17vdgtOeSvCSMpQdMzwHfA06FnZOwM5CV1rDogfGeG1T\nPOCe2qApEjR8Y+WsWHF6BfLS8vDvy/+Nbund8MmUT9z2oSmoLcCOkh3SPQ0QFy8YMLi1760RaXdr\nRwsk+EGCQafqDqwR+1gdvBhIsDcBdRei1g5bURGKn/gLeFuEjJR0zsENF3iZtVhGcK5GVjZYccnr\nazHkxVVeV5ELK8SVO9WcYuIMfHRJyNtJICatf/vdQNl2Ot3mXFUTslOMSE0wqEqWkwxiqgCZ5B6+\nUAcAyA6hQWa9TSxBSXLYG23yFc/Oqeqly9TMFvWMPLVBx4rH9BRIIPWeT1Sf8Ng+s92MBlsDtpds\nB+8coxKFQ0FNgWQY2BwWnViE/eX7oddFJ2C8/XQVrnpXLG0YypVjJYW1hahoqsCZOvfgmlpAyBPK\nQMKlnS5tVnuUxyEu2wcqDqi/wRlICLfK6kT1Cbyz+x0cqz6GNGMaVvxuRcDHYPTiNSA4mt//cnV1\n0uP8157C43u+g4Hz35uApD15DKQ3E1IquMLHJNwbdFpE5yxRzdK7bSogfW/e/86D511BlrQEA+Ze\n3Q+DvCi6lIEEgq9AQsF116PofjEv+59rT2HJ/gsYNM9VNWJktyxkekgzIekonbwY4ooVwXjM/kEs\nm5ubasKwLu4B23hD2Y2lhrBqlkbL5a4Vd+FU7SmM7+SqbMUqFGjKQAJJr+ub1VfalmJMwc7bdmLO\nyDlhbK0GQQsk+EGKSS859GrEDgXlDfjtRLnXfSx2Dgl6FvjmD8Bb0auuUDJ/Pti6OoIAACAASURB\nVOqWLoV5y5aIfB7JIxZaYP4lADRaxAFhvdWB9cc8nwPf7xLdv1Xd+IXwfzc2h/i5Azqmy7brdaxU\nSeRYab1UN1w5jRzbIxtds8WBqDJgkhnkKk+9rR6vbX8NBbUFqHWqc0h1hSpLlSRhB9Qd/AF1j4QE\nvXwFjgQWPNWCJqqNbSXbJGn7hqINUmBBEARc/PXFGP3NaDyz8RkI5Etyfh/XLL4G0xdN9/n3euKF\nzS/g1mW3gocNHC9ILupKeLP6SnmwrD5SKj0O9aSP5uofr8aMH2fgSKUot6c9EJTltryh/H3vHnB3\ns9qz5uwa2Hk7CmsLsa98H7ISRHPBzec3AwBsnA1fH/kaSwuWYuDnA7GjxLkiH8Tk3B+u/+l6fHTg\nI6w5swZ9s/rKKln4jXNFNqhAQq0rkKBvFAN9SQGkYZFAgj+VQJoOHkLdCv8CJsTr5WhJnY895dBB\nujNLV6LszbcAuKoWNNk5l/+Fj4AeXREgJcH3JFUZSLhxeCcAgMXhPSjFO1Uh5fVWfLa50O31D28f\nrvo+QRBwvER8b6dMzyV69SyLbQVVUnDmIspgM55hFHeyUFYNiXVs586h4l//igmPpnhjf4UYUBuQ\nM0Da1miXL2rYOPEarrOJ/Q8pQfzFtC9k+wUSHNcIDi2Q4AcpJr1Uok0jdpj9w37c/sl2KWd87uKD\neOjr3bJ9LCS1oWCduMERpdJKZGAZqYk9USSEedBNIzgcsBw+7HvHYD7D+T2uOuQyPvOnFJnq1x6B\nQAJRJBhVpMV0SdJJfUWzO6Vx5Ls3D5MmBGV1cimxryoPvlh3bh2+OvIVnlz/JLaViDLhN3e9iXJz\nOaqt1ZjebTpm5M8AIEb41SBqAwDoldkLgLvZItnHIaifi02OJunxPavuwc6SnXhwzYO4/qfrAbin\nWUiBhBD/fvsav4KN49Dj2eXStsPnxcGKec8eHBs2HA3rQ18GkB5iJ6j5uYQAki5Qb6vHu3veBQDk\np7tKCnpSnKihXCFSGnAGwr6yfbj6x6tx27LbpFrgFxpE5dg3R7/Bq9tfxZzfxFUlq178pugJNo0g\nCKhfs0bKgw+Wams1BrQZ4HtHNYh6wt/+t+689B4mQQzUcHWuVXfWLA6mp58WA9Gf3Ok7rYkEpfwx\nWiy84QYUP/qYX00l5Q7fWHXcr/0JlY2uIIhl9mOo/OgjAK4+stHqAKQAuPcJvtXhuvZTqNVuwW6H\n5bh7uxijGPAkisA/jBTP9+v/udmvtp8qq3fb9ur1Az1K9ktfehnLFj8JwLsiod5ix7HSemw7LZ77\n82f096s9sQ4JNj18WQ+sePSSkBzTUV2Nxq3bQnKscHLuvlko/7934CgJXcnj1kCNpUZ6TKsLxnQc\ng7sG3IW/jPgLAGDVmVXYULQBY78Ziz1le2C2m5GTmOMW4NaIHFogwQ9SElpvIIG3WFRvzLHArjNi\n1YV6iwNldRZ8seUMluyXpy9Y7LxzcO4cTFGdVVjZ8xVw3CWBZMjgO1JBaufkM5Jmi+XvvofT1/8O\nlmPhPF/Ev2sp9TuTMlrd2iRjTH429jx/OTY+NVH2rlAoEgSeR8WHH4Gr8f8cIo7catUV6HrhtEM7\njUHH4HipOIh9+Ns9PvcPBBLRP1Z9TLb9su8vAyDezP867q/Yf8d+v443f+x8jGo/ym3yRdIlPCkS\niurlNeNnrpwpPTbbzai2yKurkF9SGZT75ug3sDia7wly1LwcjEH+WdPf+Q2L9xbDsl/8Dho2blJ9\nb2mdBacr1A3wGjZuksrOqULN88JVVnZX6S7pMSm7SDwQjKwRU7pOafaxaX+FQHl799tu24iBY2WT\nvDxko3Nh11GuXkvcvG0bih58COXvvNPs9ihXvzz5RPhCIMFNfwIJ1WdE89/f3gAAsMnitc1TqQ3G\n3r0BADadOEHrmev7Oycr4aFeDc5xljsc1iUDtYsXo/S1v/n1Pk+G1Tbn9spGG8yki/ChFODMZrRp\nqsF3942WmUqWvvoqTs+4BvZS+TkimS02iUHL1ASXkqq83oq8OUux6WSFx8+z2tx/R28lOKu/FkvU\nQhDQq617ELbpwEEIdrssINI2zRQ/ZZi9IHDc/7P33YFRlOvXZ7alNwghCb0nKEUEQUEs2EURBES9\n1ot61YsNxd5FRMEOiIKiqDRpIqCAiEjvPQkkIT27Sbb3MjPfH+/UnZnNBtF7f/fj/JPs7Mzs1Pd9\nynnOg05OEujPz0xCQe7ZUc2vnvgAqu6990+xfP4OMNwzhnOMhBbhvX3vAQAG5Q6SseWMOiOevPBJ\nXN3pagDA8abj2Fi5EQDw0raXUOmqRHZStnKH5/C34VwgIQ6kJhjgCUT+z1KVPH9sQ8mgi0B7mld6\njkbd88/j9M2jQLuVEfmzjXB9fdz0SincgYhQNy4Fy7IIRDhGQgI3mfn/pkDC6keA78eJn3nK5t+Q\nBQcAissC/52TbuDYMQBApEHd0D8b4BkJXbOTAZbFdRW7EPaRifv98f3w/QNDkJViQvusZKzkRKsS\nEEJHqLRua+G98O3ejcb334f5zbfi3ibMlTYY9EpjfkAnUgs76Ur1sgGABCB4anKTJwSWZUFRwMi+\neS05dFVEO03R4GsR423Z17tVb3xxzReykghAZChoaSQsPLFQc59X/3A1fBF5SYGO11yI0v94e/fb\n+Lbo27iOdXPVZhxrOoY6Tx0++ySC234nx0ZRYWQF5GPJ44sPwRbgjl1Dc2Tw27/iihlbxAWueiBM\nghrVEyei/Pr4Si/+KkbCI78q+2/z5SrPDHqmxW0ZHx/wOAw6A94b/t6fOq4jjdpBqjAjZxbw2hha\n4ws/RwXLtYM2jhUrEa6t1fw+WqfjjNW/2RYwEtxc5vIUMY51HCOB8YrPfVIfEpxjuIC0VgfMcH29\nUILD662c7TaNOh2F9llJ6Jydgrpnn4NtwYK4tvOrOOMNrgAW7akSPrtC3HVrhpHQd+YLWPjLW+jt\nEoOQoepquDf9SrYP+GXr84EEhpsrpCyGIzXEJrhznna2OxRSslziKUPa+vRl6NpGHkgIlpWhYtw4\nobSDh8VFxlvfgYOwfSOnaf9fQtOsWRg35zl0ctWf1S44fELrvzGQ4Fi+HKGKCtky89S3FZoc56AN\na8CKVGOqZreg/NR8GHVG5KXmCZpIVe4qVLoqUdDqP1e2fA7nAglxISXBgAjDyqLHWP8c8FqG9kb/\nRWj88EMwbjdCp8ubXzkK/n0kk8VPwH8lKu++B7VPPNniiWLcZzsEdoIUX++oAMtyVMwELoMTcALN\nGCl/CXR/b2kDxZU2aNF8/ceOn/3g0N8SLCHXMRShMdh8Ao8f+gE915LsTzSF94KOWdjz4gj8mL8A\nm02TBcdOQAuPkwmQ7RlvbAfc5g3hpyMkcBGKUdrwxIgeKHrjOky+ppfmvox6nYxNEWFYsKz6/lqC\nane1QHHXQnOBBh6TLpiENFOapjPKBxKkbZsiViuKCgpRuvRLIUOuBlfIpWAk6AzEKfj62Feo88gD\nRBavBQp4GmS1LRsrN+Lx3x7H7Wtvx7XLr0UrD3DrDnKN+zSW4/uf38AldXLBPy/N17zHOXa8XwAs\nvSuuVaX1xDwjgWUY1D71FHwHDmhtFhcCkYDAPInGuJ7j8NbQtzC259gW73din4k4eNdBXNfluhZv\n+/awtzF7xGzFcpPOhPE9xwMgQeDowJOBj+W4Par71WkI6vFgQyHUv/ACKu++R/17lsW/N/9btuyM\nAwk8Eyye5ANfHsSdL8V1LhAymwB0iSQ4lxoiy7TKFUqvuBJV9xPNCl7Q9Uz0nWi3G97d2l0izqRt\noTdIo63XitSQGCBZuEsu/OnmAgloplwto5I4ldW33Ua227IFZVdfIwSZgmVlsvV5jQT+muZlJIKi\ngGG1h5E/+nLM2jwTF9cd0/w9m0tp/8RiJPDooNKakraT8cx/RD2IVnnHHbC8Pa3Zff+3wneQMOda\nB1zonX922AiARPfpv8w5Z8Nh1L/4Eiom3E4WcK+m59df4dq4UXM7/7HjqJk06b8yMPJ3otHXiApn\nBXxhH85rfZ6idE6KMBPGl8e+lDHsGv2NyEv584mVczhznAskxAG+3ktW3rB7DvmrZih4rf8ZZ1UK\nhgY+OB84+oNk4RlQHAXxIxqhmprYjnDxOsDJZQiqdgELx7SoawBfU6ZpCLKswAqRskOaPCFU23yy\n9dyBMF5bQ+r18zISJYEEB9AC5euzBaG04e9ShY+hkUC73aQm9vEnzupPChP9GZRTuNatQ6RJg1rK\nsiRwV3cI/DNsdvjQL4P8b3CTWmI14zonLRHdHKSuuPfLa+W9zzUy5JrQ6NHn3bMH3j2i0f3Id/vx\n7+8PwuIKCEJiaqUNOh2l0Dm4qjBH+D/RqINeR6EwTzTGxn5GzkVK55UdIk2D9qg7WlLMPqR05KIR\nnRHWwoN9H8SO27VrjfWUHjfvYuCbJ2bZQuUkqBlesRa5NhYUw+L6zterbl/rIRlkXsmZby9Z667F\ntcuvla3rDkcFxzyNwIwewG8ii+SpLU9pHutF9aRzQL9GeWZaxzn4EZt20EMA/5yc2iBbzAeiokHJ\nShvIfaUdDrjWrUfNI482/3sxcPf6uzF00VCkGuVZ0VkjZkGv02NU91EKTYu/Gjd1uwmXtlfWTacY\nU9A2hWiFrDi1QiEAaeR986j5IVBSguDp05rK/Dz46681zrjDbjiDTiGYAQAZCWeWLGgRe1GYG8hY\nzXd8YPwSJg437/ZwVINiGehVgnb8b/oPHQIgBhLcaoGE2v1AvTYbpPapyai65x7QLhcYvx9FBYVw\nrlkjfG/Q64SyrXihK/4RCzZOw5zNM4Vl3+2ukq3j9nPtfVXmkFjXNHhK/r7WPjVZvgI37/LXlKIo\nbH3mCowp3QoA6Oqqx0t7vtbc/+urlNdKq+2j7JjV5kI+yE9HMG2M2M1nynXaAeW/CmwkolmuJUND\nEbFr+e1YVnOe5wPKn95xwVntQNFccuQ/Bb5NK1/yKA0MS1u4RqNuyhS4N25SMBn+f8PNq27GTatu\ngjfsRbJRW08kFnJTcs/yUZ1DS3AukBAHeBqcJ6AyIfMqyltnAD89CYS8wHtdgZ+fP/Mf3PEpsCW+\nukNNuOoAZzXsH7yAwPHjZ74fzgEKnjqFsquuhnXefPX16Aiw+HZgwUjyedl9QNmvgCd+wRmBfhhU\nV6ae+9r9ODSVOBOuqHtRJQkkBCOMUH9+Wc82uKZ3LpDAGdJ+B0D/ByLafyJb7/xpLYoKCltUmhLL\nqWc5g9q7Iz6hqbghnGPLgiW0y4XapyZr91wPOEjgbuEtQmkDAHTKJNmeMDdxa2XpKC5goAeD2b9J\nMlXSTL/VinB9M+1BecM5ildcdfc9qJJkOWsdJHsVCNNCXbBRw/GPhpSdkJeRBJZlMbThBHRcYPJw\nNTFWtAIJ5rfewsmBg5o1ttqnEdXyixNyZMtNYVa4Lmc6qUcjQZ+Af/zGIDjnKzGIx9/Hyjp8PJfG\n2O0MRnQaobr9nMNzkKBPELQW+KCcTuUx21y1Wb6Aa2uJo8viOtYxxYcBAFlBDyYd+kHInuo/JhR+\nz6ZfFY4of094BILqAYOS/heA8fnA0jQxxBkGTn8Y33FZ2Rt0u5AY4vrJ8++tFoc9ThTZSIcGT9iD\nkV3J2Nw6sfUZt2w8G6h9Zgqs85T0VXvQjqxE4ni8t+89RSCLZyS4f/kFJQMuhGP5cgDA6VG3yEpH\nWI35QwjkaDBnSmxEK6Rvm77CMv54WgyVcde7Zw+KCgrR8OGH8veTZyQwclo/6/eDCQTgWrdOGMcH\nNZTgvhPrVHUPpOcdaWwUAwkBlbHgiyuBucpgTtWDDwIAgqUkoMa43Yg0kq44jR99DGz/GHBUw6Cj\nNDUPtNBn+yQAQHZAdK6k3RcyEIZp3WpyzD//DP/RqDagGo6rdf58BRtKny7PhLNcQiNcSxhMlffe\nB88lFyI7XRRo08UQMLqsm9hNge/4kJ+p3Y1B/F3lMVNCa2YGt1/UEd9NHIzhPdvgKk5wNyYiIZKw\n2TsfWPPnEwHWL79C9cSJ8PzxR+wVZw8B5lwifGyaPRvF550vY81EIz3pLKvm84GEv4GRwASDaJw1\nCxGbrdl1Y2omsSzqX30NztWrFV8JWigShqM02CxNnP1VCJa3nKV8pmAZBvbFSwTBU7PXjCAdFLou\nnLSfRIoxtvaTdGyWIi/1HCPhP4lzgYQ4wKsUqwou0kHg93eBzW/CsWQxivoOJImFPZ+37EdYFjj4\nLQlMbHgR2PL2nztoJ6khMu/4c+JdfK19qIYwDXy7NeoIfZxx7TbDf+w4GvdzEyjVgt/nBZE0DMF/\nUStwQYQY+tH9n+2+sOT/EFx+8vmuIZ1I1lfKSGD+HJWM9njh27+/+RWl4A2/5rI4fgdQs0+2qGk2\nyR5HzM04ulII0XvluSpYJRXbgRJRqT5UUYHaZ6a0PPIvsFeaOUeGJgE3/ngivJGnUbssa3nGBQ3A\noBXHFApyxdNaQnUUNxnrQWNTkQW00wnLE3eArRUN1cp/3IXSK66U0wztlcCuOcIxsGtIlovSCFg4\nfCGUN3oETQOGFUsbDHEKnhXmpeOlG4li8Xn56fBu246aRx7FnSVyiqRWIMG5+kcAzWdtQnQIRhZ4\n5LSYaXvl/Kfx7Qwat25n0SWjC+7prU4BVwPLsoLzEQ2pMxZa+wEaPvhQ/NJOjLAbfT1wbedrozcV\nEKSDSOd0TvgAwj83MOheKze0kg0awY8gMVZohsbFJ3XopOPabWowhC6tO4IbKnZhdOlW6FgGlOS5\nsEx/V7ZutV2u4fDZ5iLh/2hHomTAhah77nlYpr6N4t7n4bMtpXAFIkiHF7NNHyP1B0KPZYKcsfwn\nS1ikGNZuGAAxiPSfgmvNGjTMmIk3k25Dxwb59b+p600AgM7pnbHi1Aph+SP9H0ECK77fjM+H+hdf\nkukh8FlpTUYbb6RrBGf4utseWT0wsO1AFLQqQH5KfgvPjvstlTHQzen/WD+bi6bPlfZB2BNGw4wZ\noG2E+s74fLB+/gVqn5oM96ZNwnpXVh9QHU+kDsmpS4cjLz0Bl9UcREhFm0AL3q1/gPZ4oOPKK2iv\nVwh0sCEfsPFl4LepMOgpWTvHM8WVVeI8Orn8F2RXFAufK997H65AGLTDgbDZDNe6dar7aHhvBpiA\n3B7IGDVKvhJXkuT5/XfYly6FbxdpM9umUi40y/74GFCpDLB3lJQovHnL+fjlieHIz0yCc+3amM60\nqtimwEggx9TPUoKZvr3o2VYuoCkbJ3lsfIUkbNY+Bez/Svt340S4mjBCYumGCJAkhezfLwIAMHGw\n384W/lJGwua3ZKXKgaNH0fTJp6i88x/CsrDFIjjBUigCCdKgFsPCsWQJ6p59TrFddCDBs207Svpf\nIJSGFBf2Rs3DSm2bswX35s0ov+FGuNavb37lswDXuvUwv/YammbPQZgJ4+ofrsbwxfKAdnOBBKkm\nj7Ts7EzH6Zg49L2MhXMO2jgXSIgDabECCZEg8NtUAEDTcZL1poN6xC3PX/YbGcD2LwBWPyrs60/D\nXqlMDFtPqa4aE9F9nbUy6l6StUBiBirGjkXTAT35fTWn3e8QBaYkoJoJJEjR4CZG4YRBpI2TVUJZ\nv3jaZth8ZMBP57IyMJ09RkLd5MmovPMfygmk7hAQUu81z2dR2eaMr0UTgHkj5CUhGpR6TfgdoLgo\nLxtRmXSjjdwFN5Df5VD3wotwrVmjWcOpBSpeHYg1jwFviwM/b/hrXhkh6EAhYCJOaR5lgwHkdwLc\nzyVoONc6EIPNCBpVNh8aZs6E7eeDcE29TfwJTlWfpwUDABaOBn5+jkwm7nqJIaV+H+74YjeunPm7\nEEigGUZobeb5dmHcrTHdNgvG6begMC8dtIM4FZ0C8syIlkYCFWeb0RAdggkU2ksM3UyGZJCu289g\nfM/xQglBPHAsXYbykTfJSjx4tEoUs3klr3wD69y5ykxPoryW+Jbutyj2M2XQFDw+4HG0TRSV9B9Z\nS+7tF9d8gbt634UAHcUG4N+jkAfVrmqcPr4DTy4P4YlfyLkZJJeJUsn+9HDWYFit/D1I6NpF9tkT\niOCSuqO4qXwbystq4XJLgmS/yYMOAHGk7d8SUcg+ju340PgpTOBo7TYSjGFDvNDln5uis03EOB7a\nbqigOfCXGF3xwG2RZdh6vfIdpi8xybJMiYZEDMkbguNWkUU3KHcQxvUcB6PKVFJ+g8hE4OvKtd4z\nvjadn2ek8Ef8eHXHqwCAdkVWzDnvdSwZuURT9yPcnKCsyvsn1dcIV0s6lXAMBPNmH6zz5oPm3g3G\n5wcbJmMjbRUN2tYBFyJFynP0Hzwo+9x2xyY8t+87jCyPg7ouwcmLLwFlJDYPGwiI0w5/Tt5GGHQ6\nYWwDgKI+fRGxK3WKrPO/hHfnToBlUbtTqTfxzAHikPbISUXriNwhP1jeiNs/34Wya69D6eVXwPP7\nVs1jjhZXjFitKCrsLQRgeKed9fthfuVVzf1QB74GvlIpsaIjMOl12Pn8lUg06tErNw2+gwdRN/lp\nmKcSmy1w4gSca9fKj0uNRcG/AtzYW/3PiWj69FPFata5c5VBsfpDivUAkkF3rFrV4gw2xWlvaJVd\naSIem+Qsl3EK2iEtDF7EVWq5lXNQ+dJZLljB2wXeXbtQetnlKOnbD4HiYtmmMQMJKvfDs3UrgqWl\n0CVxbV65QALPEPUfEN9jz5YtzR46G4nAsXx5i0tK+fP4u7qy+Z0k2bh411wsLVkKAAoh5eYCCdJS\ns4+u+Ej4ny+JO2uwVwCrHgZ+uPfs7vd/FOcCCXEgNVGttIEbLPZ8oVikNZY3fvyJLLMAANg9l/yt\n2Eb+Oqr/3MHycNeBpaMG+bC6kysF7XLJRJZ4ijxvkGs6wh7OsEoUX3SWhrrTPnsIMFNZD8gbeLQ/\ngPnbTsMfEgfGQFg+SFpcZOJrx9ELg1G0//u+2gsASE/i6n95+miABBIcp5NQtDg/vprnZffJo9VF\nJOMoZA0BwGcDPr8MWPUv9X3EW9pQxxkKQYlAWksDCasfBdxchkElI8I2I2QlUEhb6sREUXQ1cfBb\n2XqCsaS1Hf/cUjo4kzsDAGYY5yCZ64TAC+o3p6Kt5wIKdhuh1kpvhSDGJRVS9POGMUuYNfyjr5HR\n5DuHNDqcOI+qQDAUBB0K4CXDt2icPh2nx9wa8/h4jDr1At4zfo424Xrht86zVsAo0fbQYiQIfdg5\nQ8gWsKHP133w7NZnsfDEQtS4a3DCegLfFn0LBkC25FloayItlFICQGZiy0TmfLtJhi9iUTpYmQHx\nvhi4m8U2VsjWYTNINu6Ogjtw3wYaE6YqmU9p+77GxC6jQEmek6QQ8NbQtzAkbwiSDEnwhr3YWrMV\njN8Pz/btwvjD0iGMXDUSU9Y8DADIcJL3Ilfi+yx5R2mIDbIU4/l98k4QuhS53oAnGMHLe77GI0dW\nIXjjVei2cyNYFjAfSEdgg3bdNQBcuOh13KLfgSSKM+QjJCsd4GndOh2YUAi0w0HaxcXoSBCNElsJ\nmkJOPGGzY86IOchKIEG4S9pd0syWzcO7c2fLugAdXwnM7AmUb5Mt1nv8+OpaklmdfCFh/CToxaDS\nrBGz8OW1XyI7KVsW9GkOaoG0ittIsFSfQcbyiN0uZBil3RrqJj6I0zeMFES/+C4IAFA2ciQcy5ej\ndPhl8O7Zo2gzKEDy+0UFhfAueV+g1wOAc9Uq0XnjAglhl/z5oz1uWL9QVzC3Pk7KBGzffgfnmp8A\nAL59cpYc6yP3Z1R2Mw5GSVSnpHBYGPuZQEBkaUnOyWTQIRhmZNv4Dx9W7LrhvfdQdd/9cG/aBFel\nOlsoI+jB7A3TkeFslC3v31SGE7V2oc7cHUO4Ljqw41yxAmBZNH5MBGVVA+oqKFqcD1eVsmRh7e5y\npCcZkZchfse3kgzXkLn29JhbUTf5adl2QgAjFELJwEFEZ4K3paIcv7ClQaH1IH32ACi7TnG2QcP0\n6ah/7nn49u6N5zQF8CUgtL2F3ayEMhztl5IPgimW07TyvOKAsV07AECoqhqB4uK4gib+w4dRfN75\n8O7S7sghA8d+jBZADJwQWWZ8dyoeQiDBoNSaUbsG1Q8+hPKRN8G/mwTGBJuDN+9UbEQ2HEZRQaFq\nNw/7osWof/El2JcsUT8nLXC2/J8NVscLq58ESHUs8M6ed1TXkSYd1CBlHA5oO0D4Xzpn8GDDYVje\nma4a4ASAsNkMx6pViuXeHTtQdPH1CLn1ol9zDjFxLpAQB5JNBmTAA5806t1+IPm7VZlxYhl1h69p\n9mzU/HuS+o8YuFo9aR/0gLZQiyp+nAQsvpPbTwhMJOo4mmIwErxNQM1+1E5+mogs8YOjQMPjBjfp\nxLH1PWDlw0TQzMbVWjWJVEGG1qnXnbu5ZVETAS8y9cfxWrz50wm8v1HcV71Tcl1YFk8uIUZL+1ZJ\nuKL6AFb99CI6upQsh8wkEzHUjq8kC/xEbNFWTJyBSE2VYhsFjq+Qf6ZVGBP8fatWV7rWJZMBsNlO\nCUbuOQhK1hOuUzOBhCNLSe2kswaguMi6GrWymWAGbxxoUfg1QcVZvsGDY6sIDBQtwyDMvXeUDix3\nDUwUjR7ZxKgbw6xDReIdSDZrq4wDgIEix7XlZAP3cxS3e50QzFCjLoKhASYsvNeshoBoQRIxDF+n\nvsDahBdw3rxu6Fm3Gvcx8VEHecMojyITbr/8ZFBc3/hMjw0jT+9AR5cZ/RtPoXWKRr9xPsgRiWBt\n+VqMX0OE49adXod3976L+cfm44nfnsCQIgbvzA2DZYCfh7yDj4fORJsfiGFjYCATPmS8XoQqKxU/\nBZDrVfvUU0K2UJ+pFKdLKK1RLGP2yA0iPpDw3EXP4fr9LHTl1UjWJ6Ffm34AgIFZBaTk68dJikBY\nfirJsA9sS8bkR399FObXXkf1PyciWEGO267TgWEZmLh2nLqEBFAMi5nzlJhVZQAAIABJREFUWi4M\nyoZD6PzcWry/gYxP0XotnQ7vBh3UwX4yFZU/xn6HIlyQJQ3kGWeCEVjnzReosJROh9rHHsfJIRej\n8eOPUX7DDaiZ9BhcP/+iuj/a48XJ4cOxd/EnGLuGdGMY6/aAoihc2v5SLLtpmSrboyWI2O2ouu9+\n1D75JABSZxuzThgQ6OJsrdLZ9Cxahu1tpuPe8+8FG4mg/x/16FZH7pO0n7ihBbeq/PobQLvEYKxU\nKBCRCJhgEKcuvgQlffuBpWk4gg70Oc3gyzVc2QcXiGNCIZkmRqi0DJZ3Sfay6u57UHrZZaq/H+1g\nVb36haITgWPpUm5lmvst+fjn27FT8/wSCgsBVx0sb72FumeeIdtHdZPRpZJ3qjCd7wrBqotAL7oN\nlF5+bPy+AkeOwPoVCfREbC5hN6P3rsI1P3wk24aNcg6lzqL9++81z2VU2R+IVJxG61plvfbHYTFT\nH6s23vXjGtXlEauVbBdvtxUAtTvEUiwd52iPqN4HT5A8E4ETJ4iOEzc2+3btgnX+l+o744IFtNsN\nxuOB+Y03xeBC1DxSdu21KL/pZtkyRYegQNR7xrH1+AAjy7WpZBkGrvXrBeHdooJC1D3/gvL4ePZc\nPAkVKfi5OkYWPGKxqAr/1r/8CkoGXCgLBHhCHpQ5ysCwDGgNoXJ9K3Jf3Bs24PQto1Fc2Bv2RYti\nHqb/CAnIun6OPQezNBAJUkLSQq0kVAClQ6imVgj68F1kdEnKAFQ0Q6/06muE/2kfeecYbnuBTahi\nB/HPQeMnyk5LPNOKtjav5yDfqbrmEw+WZYWynepHHkX1v0gQnmUYhKpbnvCkKfkYM6KjqInUJqkN\numZ0xYCcAcC6Z4B5V6vug6IozLxsJtaOJswffYzSafevm2FbsACWaeodUKoffAj1zz2vEMTky0N9\njaaWlWb/f4xzgYQ40OrEQhxOfBAD9j4jWdhVuSLPSODHQY1AQNNnn0m24TYycI6BNJCwNP4aZQDA\ngW+AYpKdYMNBhH1RL8F2JX0OAOl5vvJfwLwrESomNF7e4RVE+8IqWePNbwGHvwdmdAfWSSLxnBPb\ncCgdpWMf0KxtjNYC4AMJPg8ZvDxBcUJhWRaWg+loKkpFVYOE5pmSgMFmQoO9P18+UPXrkIncjEQ4\nZr+FosX5qNiYDd+u3+H55k0hyOJYuVI+2VnLyLWI1dnBpzJgU7EZB4ZcQr2KqAVWWBbYOYtQ6A3K\nQII4sWhH4CN2O5hlD5DaSYoSHquq++6X0/WBODQMYk8wWhBLG9SPs+6FF+H5/XdxgWBAN8NIWPEA\n6BAFOkQhwhkuHmNr6LlrreeK5hMOLoh5fDwjgaL4Mh3yp3S1qPhbO+kxIbPmb6RQtDgfvgMHgUhI\nYPhEG8w8Plj0LO7wb8StelG4KqGuBidXqAsBhU8eBN1Yi0hjI2zfLERxYW+EqqqQZCC/0ys3Q1Yj\n/0DpJszdPAPTts/FQCrKoHSbgcYSIdR06tLhWDt7Ciw+sR3iXb/SGH/fYjiCDjyylkGeHaCDOiQt\nWID++x1wLBM7vFChMMxvvImw2Yzqhx9B2bXXyQ0cZw2w+3P4Dx6Ca9160eBVuYdMk/J9Mf8iN1x1\nnJMlpZIv+60vPqBuw92978bHhRPJQm8DdJKe7iyANi9+htqH7sTF+xcLy/n2b/bVG+DQ6fBYW1IO\nYeI3TTAhUcMv+fflsUXMGt6bgZvKt2HVqm3YNeVVePzysaJ1fZVmTCzz9gmyz66qJNAhCn0ay8DQ\nABstYKfTCfRWPljj3rgRDTNmAOZjZI6gIwjX1YHx+RCuqgTd0AjLZ2JXjgzufYw0NaFTlTqF2f7d\nt4pxgvH54Fah1vKZWO8ffyBcV4fyG25E9b/Ftoksyyo7I7Dyd04Ky1tvCSr79nmfYujiE5j2NQ1T\nmEWiXhTDa0kgIVRZiZMXDQZL0zj9zGTUPTNF+C5cV4eSfv2Fz94dO+Dy2/HyYgapxyrE5bt2oaRv\nP5TdOFK2bybK8HRt2ADYysG+mgH/Fi7oHP0eUKyiFlkodeACqtHxaa1a8GOtuyBScQrsjEL5cUWJ\nfJpff53s18vNb3s+B95oBfOrL6Hq91aypjXGlKjsOFcz3zBjJlzr5YyFsCOE/tt+xNAaeVCI9noR\nKDmJigm3o3bKFPj2ifO706Jdg3/7yV8Vy1K5kpV+B5XJj0Oj7gMA2Hv1RfJFF2nuFyAlIbVPP6NK\n+8557lnN7ViWxaHjlQgkk2DMhJObMaDyMGqnTMHpMbei/sWXhPIPgDAvpNsK/3OBfP5eMl6v6Hzz\n9593IFXKC9QYCbZTyfCaOSHDEOfE8rR/nia/bRtqn3wK1s9Fxqxz5UpErPJxlw9mRBoawTIMzG+8\noWidqQbBIokRSDC//gbKRowgNhVAkiwNRYQtAgjXIUgHMWLZCNyy+hYM/m4wHvlVXRdAn0aCOlLm\ni/n1N2Iep6ENYdlpdoTiULMzG6dW5kkCCZI5JhyWs0F1OpRddZUQ9BHurdtN7rdkXW9UOU5YxQEX\nWCi8DcmJ8UrB+rl3WK10lrPTmmbNinmO0WB5W1UjYWT78kuUXDAAwVOn4Nm8WZiHmmbPQdnV12gm\nFzR/j/vLm19XdxKDBQ/1fQirb1mNPm36kHGqRh6ACZSUCNfkms7XoGN6RwDAlvFbsGX8Fo0f5Bmv\n6uNoxM6VkEW9d8J1odBiVq596dLmhUv/B3EukNAcvE1otYVkh9rXbwA2vUZo7kfkNCK3OUVwNOr3\nZsLXYEJR/yHwbV0PbHkHti/FAb3xw4+Az4Zxn7iXmG/BVSaqjvv27hREDmPC0yCrqY/Y7Sh+bAkq\nNrSRreaqThKCG/6jRwU1ZrxfAJRulB2GMIHxzmQVoYax8VB9uFNyniZZeN5IpN1u2L5ZCGdFEqEN\nzb9KvhlLLCn+xV60R2QL6C1HYStJRePhdDz57U70aZeBAR0zhbITgFDb7xoiZrBu6kscuPpPiYPh\nt5pQuYpG9VyR5mZftAxNEzn16l1zgE8GAIcXiSUGUryWAax5XPzMMiSoULNfYigzqlkfvsd5uE4l\nkFB/CPjlBVKTxQeU1EobpJP2axkkcsvh1MWXoPr31uQDpZORF6S0Ps+27bLP3t17ULm5tSz+IQ6k\nIk3ed0Bef6sKrrSBtjahbORIRa2yc8UKVD8kKf0QGAmiRkLtM1NQVFAon6TsFTi5Ig8nF+oR8fgR\ndBqgByPQVYMO8gxQAQcwawhgUa+RNoDGqzf1RshI7gUdUh/+Km6bAJZl4Son51P50JMAHRJ8A8ZL\n3o2I3Y6iArkx/5RZ3h0gsUrJkqGdTpRcOBClN9+B0zdehVOXDoflbSKu6j98RAxGsYyo8A2AkjCi\nqiQiUABIqdCsi2RdLSb9xOASYwG6Z3aHnmZx0x7yHNF+H3TcTzQcSYdl5TE4v5BH7e2LF8P+/few\nf/cdfFxWhZWKin1/G7D+Geggr02ueexx1ES1FY2HVpy8bCP8u36XLfNu346mJ6fgmUHPIA18aZIL\nSU1ils6dDPi374Dr9wPwrv0ezy6j0b6RRbiCaA3YV27AVxlpOMxpMLQzcV0q9HpMXqlCf88BRmQc\ngCMzFRldvKjsq95W6pEjqzB38wxk/LgUbIPyHvOMJykSOrdHSqWy7aa9NAX3blsP+8lUOMrl9O+w\nZPyXOhXhmhqEv5mIio//gOfhfJReOQIlFw3Grzu+AwB0MwODi8n5hdx6VP/rYZwadikqJtwOJhSC\nY/lyRLZ/DUzNB078CPObU1Ex4XaEKirABAIIVVXBPHUqav71sCD+BRAn6fStY4XPZdcR5opfQqt3\nLFmKU8MuldO0uWe6aY02a8i9aRMCP74vfM5xEM2EUE0NGL8fBhqoHNgOhpwczX1k3XG77LN90WIE\n1mgEsjnQDidM67cpllfdSxxWNCPuVvvY42CL18NRloyKf70I2zffKFgzCekRpfYPy7ck9KNocT6Y\nEEBxQdG0q+VzI48bRk1HIhNCuNqM4qWi1gXt8Siy8vzveTZxjvo+kjW3L1kOb30iwn7yTlVtaYWQ\nywhDW/U6Y2ngxGvRVuK3vPkWTo8aBf+hQ3D9uEbGyjCUtyyDmXTtdeT36hNly49dNQ7Hh1yHB8dO\nwyWrlyCpn1LFvftW+Tji3rBBlUWWMmQIemxTN/pphwMJt14Hk1kMgLy852vhGrs3b5aNzVKwwaDg\nTIarq0E7HKh7mpurGUbCSKABT4MguqeGUG0tigoKYV9MbJiINwjL/kxUbSEOMp9woJJJNpx2kgBz\nuI50p+Br/HmcGjpM9pkPZkSsVoSrq2H/fhGqH5E78t49exAJRs2V/L1VYzxKQDtd8L40BPUvvwLM\nv5qUtXLgGSYnGo7BF+YYMHQAO+pid5OKpqr7Dx8G4/WiYeZMkkGXOOF8copulAcSaiY9hpPDLhWC\nAJ4arnWslyt7lMxZEZtdZtMpygskz1bx+X1UgwWABtsRhJlUefc94F3tcF29gn3DBrl5Vo2tIQkE\n8IEkx6pVcP0sBgDZcFj5+9x1ojQSRnxgObo9qHcnYUpFuHIix6pVcbUQZbjz65zWCTtu34Hh7Yej\nY1pHvNL5X7iZ6QP/4cOK0h4A8O3bh9OjboF94beK7zITM9E6qbX6DwptddUTVHwlrnfHThQVFArv\njFDyAcRVTtw093NU3PkPsCwL8yuvovqBBxGx2VA+ZoxCM+V/FecCCbHAssAsMeJ9rO0oYNsH4vcZ\nROjPbzWiZksGItzEHLCZULmZDPTO6Q+h+o25sLwrGkgAADNXAyvQwZUDcuXGVii7Sp3iwyNQdBz0\n1J7ASrF1XvjQb6rr2kpSUdR/CGiHHRXjxpOIqt8Br9mEgJ1zxkIkuMBs4GqY9LwzyRlBQS9CNdrZ\nBSKwqHz5fPv24OSgi2B5+23U7cpC+S9tgLR8YM3joLfNh2/fPlAuznn0iwwBJhRC7eSnkTtfzAol\nB52IMCxapSSgTzuRSk1RQLJJnNyNsRTPJYdoOxQAin4iwnr8sp9+U61HZvctEP+f0Rt4twsw70qR\nScIyqmwGPkvv3rBB8Z3gOPqaAANHj7McB+q5yDsvABQ9IEZ1BvE1JMBvM6L4o3rQAfHcqcQEoksw\nrQOqJ06E+VVRbMoybRp8DQloOpEKGz9Q06IjCwDmqVNReccdsEybJrA3QhUVKBsxDN5PHxQPgJvQ\nnGvXIVRahtNjboXt66+Jg1KlLCExT30Hp8eNF8UWfT64OApyzeNPEPpo1LXMmLsD5etzoGfDYENc\nG0tzIiIBHVD+G9BYBGxRp7KN7dcW6YlGhDnjIuLXfj7YYBABm07y2SeUNvB0PzVRN+l1BwAqSiOE\njURIfTQ34Yddsq/BeNwAy4KJUAhOGwK2UT07pNafmg5TYKIo5s+vNeHLhAew6F3RAMnyiCKD7hpi\nqPtr5FF57x/EsdI3iEEnKVVcYOU0yoWa2GAQ7l9+EY7Rf/RYs8YmD8dbd8H20h2q3zF+cr3cxXZk\nV4iGZBeRcIGaba1wYSmL9+fRoD3i+aTbKWS5Oaq8njih+hoL+laIBqfeRK7Py3fp8ULSYnS9tgH5\ng52w9WxeK0LtXthKxEBCYmFP9Bpbjy4X7UFChvJa+CwkyNFwOB2NR9IV3/MIRwWVbQe88DcloHor\nZ0hFIug6QyzD4gMl9XszZaJdnt+2oP7Fl1D7/Otg/F6wi+8SvrPO/xIl/S9A2TXXwrmc7Ct4UjTu\nGK9PoNIC6nRzXqTVvVk6D7EI+3Ww/qRdw13z70lwlotO1fvzaBjsbpRddTVKLhiALGcEEZMePaIc\nRQAoKDqBwuIiZNxwpWy55a23NH+PR6SpCVnrY5dFNYdTj8+HeR95VixvT0OkgTyYeVOnQp9AI+RR\nOp3Wzz9H1f3/RMnox4RliVn8eKduwN5r2IDuduX8e3LgoJjHR3u8imwmn/jwmskYkDw4dnYfAKp+\ny0awSR4QoYWuDvJnQcoCaQmcrdqCSVN/D6yMHv4wCyaV+16nvK6G1krHgg2GYMiTM8N0CEKvsi6g\nwRyU7i9Gjb/5tdeFObvq/n+i/pVXZewMnokSMZsRmdoLOkqdJQQANRydnC+nObVSDGyGvXohkKCL\nkLGZcZBxmXaIuhIKZstOMXMt1XDgnW4+UA6QwGHV3feganPUdeI1EuIQ+Kv6LRuOZcsUpbb885J4\nxT/w4M9y2+aHkz9gyedPyZ12vi1q1LWvuG0CGj78CNYv5sE17S7gdXHM5hkh0UwM98aNoJuaUNyn\nr0w8kXZw60nmrLrnnpU928EiUS8BaKYMQgLPr0rmDQ/fnj2CHopj6VIES6K6iXBBQSZMiXYaB12S\nGHymXS4wXi/qn3setU+Q0jP/8eM4PeZWlPTtB5dUZ4Q/R50ebDiMU5cORw23DSCW4wZ2i8cdsdsV\nrYnrn3se1RMnKk+qbDNJeHmtoJ1OmL4hegSdT9iR5A4hzZSGtWPW4vyHPkXFmFtRcdsERWkPAIQ4\nYVrvnt2wfbOQMBPoCNECs8ZgzwgMWfVnVOcn77h1PrnugjYc0zJGQuMHH8C/f78s0Vc35VkETxQp\nNFP+V3EukBALYT/gEwegkrqoOrJUEsFXMxJ4uCqT4KlL1PxeQFQgQcZs+uYW4MvrVDc7PXosTm9s\nAxz7AXSIULGd78em5gb3E9YD7XCALd2Eqi3ZOP1LDugQBZ2By1oeIZG06G4D/tNWlF11lSDq46lP\ngMcs1mt7zeq12/YXxsnPL6ID63cD+xegcvI0VP7jLug4Me1e+99Da5CJsOa9mXCtXYvy9WIW6vGV\nn0LndSHXUQ99JAw99+InWS3os+pLPL3/e5w23oELyuZoX4Qoii276E7hfyYCWD76ClX33itrPdh4\nNA3FS/KFgJFsH7zug88KMCoZLH7iDYflk1okBGx4hfxPh0VGwrqngbnD4T96VHAgpHoHvgYT/Dal\n+rj9ZArYCBD2ikwNfXoGGXSDLsX6pg4kGNZ0LB0WTn1aOFbu9zxbiOFu+/obgUpoeWc6QrVWVH0q\nZnT4ZyUg6fZgmfYO/IcOof7Fl4Rl3gYTIkEd7EtXIHD0qKBQL0WwuBgl/frDt3cXKqONGAB6nxfh\nrWLdbSSgE8tCaFHvQGoAPDwoHckmPTIY4pRG/HoEXUqBJACkDZNZHB4Zj1swvPkgAK9fIIWtJBXV\nW0XBICrqWbB/NReWaepCQwAQPHUSzsONKPkhD+Xr2oI5pOw/LUXEZhPq0ys2Ziu+9+8/APMTk2XL\nutazQgtFJqw+BfCCUg2rxRaZtFP+/LA00DDvB6hi9iWo+sd4VIwbF7eh5ShNgeUHJfMlWFqKkvHP\nwbw/AzW/ihnRcI5cj4GJqJ/LJYuTMfdTGmk+FjlcuZehSe789xhtwddPMAiaKNAA2nKlIyYqgkAz\n3StYh7qYE4/MqwZDZ2BB6QBTWgSp+QG06etCl+tIRsdr0dC7aAYRu/J9jsbSaRH4GuT752nYQZcB\np1bnyjLbjmVyRg0g0txpjwdV92iX24UtFviPHIExn+yv8YMPhMCj63A9gs74u4Dw8C4Wj8cYAfQB\n8j51XrYMWXfcDlOXLsh+5GGhJCZx+79V9xMLEXM9QqYW6sFEgXZHMXMeeZQcT5/zkdYuAJZWPpu0\n0ykotfNIbkvGwowL2wrtkE3ZYu31q8aFyLso9vOmBsbnBcLyensmQsGxfLnwOaTRvjUaNUvkGddA\ngvrzyzSnB6SBBQ/PRFnrzkjIImN3Wg/ytzw9DzNT+iMQoZFgJNcz/TqxZWzum2+g4NhRVaaAb9cu\npF42HPmSEgTqy8sVXTlS8rjg9E5Rn2JfTi84OisZRoGiYsUygAhpShGdPJA6XadW5iLibn58ZH0+\nRaCmdE1bhJc8RT40kPJOetf3pFWxJHhQ3EfO2mB+elH8wAcSwmGxDEPqqHPLFO8un9xQCxJHOV+8\n/kZ04J4JhRDg9I+uOiQ3yF7f+Tr6vr8elrenCW2FY4lE823J9fVcKQEvaMldB6nNFV26YZk+XTwm\ne6NsOwDw7dwlONVqiA5SaEGfKQY4KI13hkfFeLGjFEvT8GwTGVOWqVNxetx4NHzwIViWlWkz0E4n\ngqcrxM8OBypuHStk+msnPSYEf3iGgi7BhPLRoxFpbBRa1AJigMS1RQyCnbr4EsH+sbz7rirLwvrV\nAviPHYfl9ZdRuzMT7uULcHLoMOgs5Drp7E5UTLhdsZ0W+JJZz6ZfYXn7bVT/cyJOX9oLwS2LgRUP\nxtiOLxURnxva40FRQSEcK1aC0nOMMF40WBgKuFJAvw7Q6eH44Qc4VqxU/xFJeXawTNR4kbbCLhsp\nL437X8S5QEIscMI2dG5/lDO5SEaUw5OeDwx9HOG8GzV3oWXcAkB4ShZ8xSRTG6k+haLF+bCVpIBl\nIIsAN6zcB1RpCy+FPcSh4bNg9lOxW6g0fSMa/6EKMcvlbzJBx6Uq6ZAO/r3bJYwEeVTPu5FMltW/\nt0b1ltYI+3Tw24xEoEQFakakpzIk+05nJG9ySoUP3656EyWhu+BdqFSpTXE7MeObp3HnnCko6dcf\nw+qJs9Nj9TfotvUnjKg+gIYj6eh1QF3xGpA72gBAG8VIPx8oYAIBYM5QhDx6BJ0GNB2X93lmWYAO\nUqja0grh8uOSnUmcx0iQ9LAvF2vlZMJkx5YDldwkwUQAo1ywp2LceMl+aQSKi0GbK1G5OVsoXZGq\np6sFcnTJyWAZsT2pFF6un7ZwTpEI2EhI+B8gmRPhdBoa4N78m7wtUQlX+6tB9QQgU5Ou2pyN07+I\nTm8sES3vjh0KRwgAzPsy4DwmMldO/5wDvy0RpWtyUPLOUdiXLkVJ334oHTECQoTKVYcBeyfjZooY\n7+6aJDjLlQJJamDcLkkgwYOGDz5E4Phx1XU9dYkoWpyPosX50EUFEiwzNXRKONi/X4y6XaLYV8ii\n7SwW9T4Ppy4ZipNDLkYkoEPIFZ+j9uRqDaqfiUG7S7iMlkqWPXjyJLDrMzDb56BhL2AvTxbGr2g0\nbKpC4BT5ju9yMvtGHRaMaPmU43iGZJmjx7W83kpxtliY/xGNQi5QoQ+RZzs1P4CuN1hAUUABp3If\nkDgXJoTx3oWEJaFPUM9s5ET1oo9Gil/s1EPpgA7Dbcju7UFiZnwBFi1oqeA3Bz4wSQf0moEk2fr1\n9fDu2gXnqtWazzwAlF52OSrG3yZzwiINDQibzahdeBjVW+QBwcTzz0fhrl/QbaQlelcCrJ/JWVed\nD9QD5qNI6nM+cl95Bd3Wr0Obx8SMPmWPv6sFD8+27aB8zbccPhMkdO2KjM7+5lfkkNnVh4Lb6pBW\n8S66fj0L7d58Drmje0FvYtD9ZjIOp+Y3f6ztLvejYHyd8JnxeOGtDiHsE+93xcY2sgBvoKhILGBu\nAbr3rYW+cwtaanCgJj2Fmsx8WF+ajk7ff4fS3oPxfc+rkJlsxPoTdeh6bRMKJ9TB1JrrtpOZhrDe\ngDRvNQaiCKjZh8RCsbQsoXt3Iauemh9V9xwOI/vBB5Fxk2jU6zhHIv1G0X4zcIK5De/NENdjWfTM\nUrJAzK+91uJzPlPo22QjVKs8htLPLfAf2CeQGmlzBTBrMNj9SruJR8Ap2j4CIyESEQWH/T6BcaYa\nKICoAxE4LmHlVe8BfDYlLZ8LogkJGA7eHTtQv3uL8Pm+80kpUbaTRaZHfA6dP/G6X9olRkGuhSEv\noAyuQwDvDPNlebTTifIozZNIg9gthF5OSld5AUUedpUAK39MDo1uCV3Xk5Kq1CsuByAP0rafHb+e\ngWvdOljekwubBo4ehXXuXJSOGCG73hGrFQ3viIkKy4wZiEbxeeeTaym5t6FSMbgiaD741cctPigR\nOHxE1LvgwIRCaJg+HRVjx8K2xwZXZTJq3p6nYCWGq6vhXLu22ZIIxudDw4fyc/fu2IGAzYTy9Tnw\n1oRF4UdvE3y//ojyUbcQNqvQul4cm3imkfXL+UIZGd9OtP6550G73ULStOFwBliGQv1LL6P+BRWh\nUgDsXFEw0r1JZHtIbeZQaRmsCxbEPM//61BPx50DQdgPpObC1+F2uKo/Q5IuyuHpdztQcAPofdMA\naDv6PJKyg/A3EaeIZYDSH3MBNCFvcBKYk4cAZMJyMAO+JhN8jaLzZC1KQ04/ZXRfKsjitxoVjq4W\ngmVi/bm03oyJiIyE+t1ZwG4xcs7Wy43lpm9WwDhYdMJK17QFWO2sjlogoeaP1jJjx1NDHkc/d+7l\n6868N6ytJBW2klQUXKM+AEQj0MigekM+8gbbhWvAuFwomgUAGsfBUnCcTobXnAjb8l/QlveNpXT2\naR0AOgi2PBUAoWM2zZqN1BFXIqlPH6DBBl1AB0MiAzScABIzwbKA7WQK9Ea5ccbSNCpuGR11DCyq\nxopZmUhA6cyzkQhqd2bBXa10mqOzRoHt6xA6TZ4P2mpViv54HaiR1FAakyPAognAa05N0R41RHzi\n0CNtraRYT4Ni6q5RnkvFT3wQixV6hUcam0SGiKsWrUrWo4kW35OQN74hsPS+lwCQ7WiHE9a5c+Pa\nLmvvn2sfZN3RqP2lZII8/Usbxdep7fzw1MYXKAGAXmPMMRt61D3zDPTDrfBbTbAeTwOgTfu3nhCv\nsXMlieZvL6QQNlJIDAMTtoo/tLE/hasPaTswtiL1wGib3CB0j96PhlnqiumfjNRh0k/aJ5SUHUKH\n4aIQZBL3rPspCinc/zfrd+Kl/Ptxwy3v4nTiP1C0mGTbU3ID0BlYuGuSMPgIofDvPG8A7uz0M6p+\nay0zmg3O/YBGjC2zqxeO8tiBX0rHanYC+jvgWrNGKDmKB/79ol6C+bXX0ebxxxTrtB3oR9bCpUDd\nAZhSaWR0DcFZrl1/L8Nnw8h4c5YQqqqCPkM+DpjSw4rA3NvjdTBFgM+nbMd3L43HoE3N1/1TBgOS\nc9QDpfrsbNBNTUjICIOhKXS41AZTqhisSvhxJBIAILMTeo4RDVPNDVAcAAAgAElEQVSdsXmnXZ+S\nCEoHtOnnQuPhdFTcfjsYZxr4MUwN7YdZEfIY0HBQZPqk9cmB+2gDOi9bBvunb8P5u8gYMqVF0O1G\nMr7VBLIFMVtDckQ2vmfech38W9Yg6DAis5sXjjLyvBc8+gAKHn1AWO/CL+dg0jub8Wa7DBglAVhT\nfhCp+RRu6/cHvjHegndqOcblPABPiK34eCYMORcb6JAOzoIP0PDOdNn3iX36IHD0KJnnG08i/zIG\n6X3uQc07XyOzq09WXgMAHd0WmFKap/D/lUgsKBTal0bDuWwRmAh5Vh3lKXDMCQLRSS8JvPWJSAqF\nQJlMgnZEuLpazC6zAH64D7h7tax0IRKkoA+HQRmN0KelIeL3o/6FF5A5hrNJ5l+NkKkXfHvVmSiR\ngA5hCSuh/rnnZd+3SiBMvtmzo4U/iY2oJkYZDZY1AQiQLmSpOTK2Y90LLyJ5wAWKbUIShoKrnELD\nXXeTxIdOByohAazfL3O0pXAtVk9W5b/3HhK6dEG3D/4F5pc34EEO3BtJQDnrrruQ3FGZ1NFCrBKh\nSF297Bxrn3hSZtM5f1iuthmaPpsriPdGosohzVOnovW998bFKAqekrOYSvr2a3YbHlq0/7BfB2MS\np6nz+ecxy4yqljQCS65BYXER8GEfVC4kNklJv/7Im0rK2jy//w42FIJ3715xX+GIEEhkJGLrp4YP\nB+sXn7PiD0T/hOXeGeEzTaNG0uElGIPRRRlazsb7v4RzjIRYaN0Nkft3ombyR6D2Mbhcfxgsq4N5\nXwYCSQOBnsSB4+vRAMDUqZPW3pCcE0LeYOK4S2np9lMpCEqMFjWHz16ajJILB4L2eOD8di5x8MpF\nWnnNH7H7r0oRaRKDB7RVEo0N6zTLMBi3Unm9frf4EsUKIsRCyQp1MbOzBWabUtxMDdUbiOFTvzsL\ntdvju5YsA8HApxg/PPUJcFYkgXmnAK6qRHjqE0Qpbsn1ca1bh7rJT6PsmmtR9tinOLUqF/bSZDAR\nCg27aRQvyUfDwQzU78mS/57aRBryIlARm1pX9/TTqs+UGioeEpWsa598CvUvvCj73n9cTudkaMl9\nj6OvsxrcMWoH3VvVhZda4ljV7cqE5VA6LO9/gtLVuXCUioZivNelOWT19ECoF/gLkD/9HST37aX5\nfXS2BwAyusSfCc0+j+/SEnu96q2tVQOWrXs3b3TQ3CGuGKrDrl7k/j1zvx5fXK9HTv8zcwxb26Yh\npb36dd95XuxtTanyLEkiH0iICogdSXwAUwzyrFP7YXa0G2pHRKdHWsADf0YGRvbdhYT0CIzJxBDu\nPsqMwgl1amXcAnIHOZE/xI78IXYYU8jxmNLD6DFadBwLxtej5+h6ZPX0QG+KM/Pbo4vqYsqobdC0\n6qVs1aaFzK4iCyrnAu1759uzB5XRwqAA0ts5Ca3cQ+af6IDeB6PUH8Qll+o0e9eY7WVYl5KMNkPt\nWHKpfPuT+cC/HlXeiMSBA4BwGEZvCM4sE3TJSegx2owOlyrnu0PddNjTS4dKyoYDt/YWlqd1iHrP\nuKx4zgVO4JOBsq/aDbUhNT+Azp+8ivRrif2Q2dWH7iMbVPUzAAAOuTq69HnSJ9BI76h8z/UpZFxL\nas1lmVUYRlK06uVBWrsgWvfyonCCaDy3630IBa9egKTlQ5HcWmRHJbYKocs1ou3gC2lTtXPvHIq2\n3DOS1cOruR4vnBwM02hlFOe6TJMPHYbbYEyhsUEfVbYZEvenz5DoJekAQyIDU66k3OvQIuD4KnRe\nugQF4+tIZ7dD34E6MB9pFdPw4ZjbkJwdhj5R7shmB5xIaiMPBiWrN+I5q8joLJYYBIuOgOE0anjW\nGA9juh6MNqlPgabjaajjnXhJW0ybpIUl28S1k5SwAE6tzENxn74IWxoEoT2AiKQyfj+qfmuNsm/E\neSCzu/xeR/x6uKu1y3yvN16ApdOU7wAb4FvjBpF4Xm/0eHm45j5oNhkBuwENs+eBZVkhCAEQsef6\nl17W3BYgIrk8e1KflorM6y6PuX7d1I9Vl/PMF5Nlo+Cw8tey7bNTQM3TPoeWImwR74XM+TdoJ0ma\nZs0SStZs8+bLvnMsXoKy666X6Xpowf7dd8L/ChHKM0Tp6lwEXXqcHDxEViYbC6GKCoSdcvtYyrYq\n7tsP1f+cKNz/UGWlzOfiIQ0iKH5DovPV+MmnKD7vfFmixh3V3Ua232ih3f8xnAskNIPSyy4HAOia\nyIAbsOthL03B6a/qAJ0eTDCIMEdjMXbogKSBF2ruS6dnkZxNRvzKTWIGMegwwnk6tkNj3pcJxuuF\n+aFbUPfWh6i+63awX4nCJGqZaADI6hHbOKydKwpimfdmalJdnadjZ83OFGyM0o+zAfup+Fga8cCQ\nRCOxlThj+xpN8DWQCCXjaET1761RtysLJcvzULujldhFAbyPre1omvdlouSHPFiLtI/Xv2+XcmE4\nfmfxTMBnkwVEBYzokI40qggEBHG2lMuanyQTsyTiRSXa1HAm2AILSQPOimTYilNlAni8uB6Prtc3\nyO6tKa2FtHOGQs/RSvV+Hnw9PA+qhUGHjFGjkHO3dgmVGpIk19iQHAEoFgkZ6vRQPpBwJsgbbEd2\nHIEEaezng9E6THhWj8q2ZGGrXl7kD7HDkEijs8RBSe+oLWoGAGBptOqu3j87oqFGrU/kNEB4n3wI\nYdgkcQwPv0o05WGDPCNP6VlQFJCYQK5xK2MjcliiDN5+mA15gxyo7TVasR/cy6k4p7cDAFwa+hAZ\nnf3I6OxH2lVEqb/TlVYYEhh0vb4BXa4lz40+gUXuABd6jjGj55h6oZ5T6tB/zZWN6FuFUXh1PdLa\ny8eGdtPfRMrg/tCCNEiRds01SM4JCo6oFAk9eyC7D7nfHb/6Eq17aTuHamjVy0PuQemvwHZCW23b\nz46UbunoNa4OhRPqMDlDvdwhYAJ2J6o7rf9edgOezcmGtWsEy4eJ93B/dwrTx+lhSxcfwDk36DD5\nn3p4BpLgXJKfRtXgjui16QcYEhgYU7Uz0KNWjULnIyuwuxeF0n4mtB9qR/dHOgvfZ47julowAKyE\nBtxpRBOyenqQ3iGADsNtSNKdQnI7cowJvMBi/38AfdWzztHoeHkTut9kRs/RFrS7xI5uN1pk94/v\nBMCz69TA0/jV1ms/zIYO1+tAUQBVQp7ZDKOYuMjp54LOKG5T0Un0rHMvFIMWbV98HtTyfyKlbQiF\nE+qEch5KzwIV24Ha/cCy+4DXMpBi1CPRqIPZGUCXovgYX1LoEpVOamIHkqHUt8kGVv0LWHYPKIoS\nA6YSbap3kolTREfZUsb8fBgSGNm4FJO6pYEuqzTqrAFkjpNrSGUV0si7yIHWhW4kZIQRkWi6JESV\nRLm370OwPnagqOOX85F+/TXCZ74lt2e7WHsvbU9a/HkYbCgkCOdK0ThTTpev+fcklFwwQKH1kjdQ\nfkwRvw6GJO3rptuo7JwCAAzn3LHBIPTJJhhOLYYpQ/25tuzQ4fQvObAuWY/A8RMI1WizhiiV50UK\nPWODqWqRYnnuqy8qgjlSFBZLGJZMRBacTxl+KSiDQdYMIKGV3KbqdfgQWj+gIl4IwJiqtEvsCxcq\nliX06I6UoZdoHqMUsUpGWoLGT+RlmznXyYPZjodGY+MF8SWAyte15TRkmmd6A6R7EGF4xw+15EvM\n9a3iPbd+8UWMNZUQ2mP/j+JcICEG2EhEeMkMXgauqkSEJcKKJYOHoHTEVfDt3o2UYcPQfeOGmBQW\npttImNKUBgrLUKpiTF2fugjdR8mdk0g1qQv27juMxmOxneT0jj60nfp+zHX+aqhlSwAgpcPfQ/Vp\nPBI/haw50CEKHa8Qs/+WA5mC4rX9gLYjFXQaCNX7T7CTdSYGjbM+VyxnPC0X3jqrYCkUL82H5RWx\nFWWHTz6RrZIx9lbh/8SCbgCAgD0+GjMbkEdyo7NFPFJym6c9SpHYWj55UjoWrXp6kdSLiE8aUyPI\nPr95MTseTISC3sgKmTfZvvWMwlCPlZmLRnBIHwBAUvtUFE6oQ/ebzcjs7kX7S2MzUQzJDAonEMes\nx80NKLytHh2vlLTB4uqhW/eXMxH4IAsvPNa60E2cVw2ktw80y2SImFhZK6U7XW4wXOb/U3MDKArI\nGH0retxiQVKrsODAttJwUvnsPQCktA0i90JCz8x77SW0v6M79t5IypEmPqbHx4/J2wWmcs9KRhc/\n0P9O4LppQFYXoZxhJ7phK90H22htSgN/KrzzJg3QGJIYZHbzob5NVKu19hcBnYcBj+4BJh3AtMG7\nUMPmoIwhTljO44+i+01mUuYEICEjgsQspeGob52LtndcRs6hqw+GkVZ8dLMO6wZR+GSMET2ubgRs\n5Qhx2jk5/Vzo9cL5SLd9hXa5Pyr21/5SKzK7etGqwCNc9/Yff4ROV1qhi2JApF05HF2fvQrGJPJs\npeSR73uNja1yzyMhLx1tL3CR6/ftGKCKMI6SWgXRcVCxkG3vFQqjw2VWZPX0IH+wXXivvImAQ68n\nuixeeUu3RgPZeGk6GfNPFDCYdaMO08fp0cpIruPhzuTG/dZPh+ocCgtLRaZJbpuuYks0CujyqPz+\n95IENY8mJGDmGD2W3UDGMYpL/hlbpyChKxnjQm4xI5jcJoTcAZLx5I8ZSK+aju6jzEjhSx+GPQlk\ndozrOqbkhmBMEe+NKY1GzzFmoexB5yCU/8RM8bnM6uElbIirG8mYMMoisCmiA5tp7QNI7Syfo6XO\nDy9UxsOamomC8XXoeHkT0toFkdqd6HcY6jYiGj1uMaPHKDOw4AbgiyuB4yQArQ+7cU/GEfirD4GK\nxBkgP7k+5tfGgx+i1/596LFV1CjCbsk8ulN0fjL0yqCZKT2MzhcdACBeo6weHkS8zQcSuqxYjoLx\ndWg/zIb2n3wME1MhfJd61QjZum2fE5mAeYPtaNvXAkoH5PRzK4J50rEPAPyl9aB9sZ3BxC5t0S7j\na+GzISsZTCiEiLQddRSjsP7lV+CITiQAYCvic+4AyDQ3rMVpiva2ANHOAQD7IqXTDgDeU8V449Ur\nUVl3Ak0UeS7aX9KIjNGj0eOPrarbAEDF2LExs8Smzp2RdCFJ/KV0y1B8rzMxyOruQ9Y/CKOqy+rV\n6HXoILK6uFUDdKolRwwtYypGmuRjliE5gtY9iYOaOW4cuq5fB11CAnIeuAMFE1l0uMyKVrePEdaX\nsoBigQkEkXLR4LjWjQfSoKMmojp4pJ6fS95zDpH0FJTm/edK9P4saBffGjQiaLHwSB40UG0TAWqC\n4v9LOBdIiIFoOkrtjlayqCvjdILmBga+/i6pr7KvMY+wj5uY4xQ0SujcQagV4iEVnlPrVS5F/k15\noHqo96P+q5GYFULXl0cKdUrR6PhQ7BdPtu6VTQqaHAD0GF2vOsBFL0tuE0S3CeoDWPetv8OYKTq1\nxo7ahlxKbhB6Y8syyZ76BFiLuPvEUsgd6Ii9gQYyNAIyTfMWxNwuq2f8dOWWIG/aNFkW2/GjRFCO\nlb83fHuipOwQ0oySGtt00fiJhxoPAD1ulmcqKQODXuPqZLXu8cAY9YzoTAwyOvvR+UoL2l0RRLuL\n7WhzvkdG8wWUTAU+2JCSS86Zd3yNKRGBDZSaF5QZ3m36uJDT36Vw0gDg7fuBw12ByRPFgOX0LsdR\n8XEfoJRcY2Myg7yBTqTmide5cEIdto4mz5mrvx/Zl7ZWbYGsN4nH0fFyKwrfuhg5i4uA+34GXqgH\nOgxBzgUu4bgBwJBMy7aLBsV1JOChljXJ6eLF7goxO9RhuFgy05uvze0hZsw6X92Ewl0bkPhPeVBK\nOHZJQI+igKx+ySgsLkLmhDuR9soaVI0j454rhcILt81F52saBbHExFZhFE6oI+d3C1f6lJCKNI6R\n8AYzHneHn8f7EXmWUP3kyR/e+ZfCmyjJkIx4Bfgnp97ephdgTISJE7L9JEKYC1TrzjBO2R29Gzku\nmQRMLkbWyMvQ5boGJGeHYcsGtp+nA0tRCHWOCPedL7HI7OaFrnwDULlNZgDrDAw6XdWItHZB5F3k\nhE5Pxtqe0ySCdJL1e42rQ/v7BwMbJfTgBTco1ms/zIYuK1egy4rlyHvxKWF5p6sa0eni2MKUUqTm\nBZE7wIWMLn5k9fDi45t0+L0PhRBFEV2Wb0UDGwwj2Ov8Y3/RwCYMu+ISzOpwMz43E2bHu2N1eHCS\nHtd2JmUFYYk9eF67ATKh3ETrRnS/yYLuo4jj+0OdaBTvSSIB5ADXCcfQsAM5FzjRadJwJF5MWjGG\n85pnNcnmd50eSFFqnWiin7JVahY3T/LzFKUjbCtQJJDQYbgNSZIgaps+LhiSI0jJUzF0dUpqdO5A\nB5KyQ0iIGgcfNqwBpSMBDgCgA+S8DJVKR86QyKiPJ45qPO95G1MtD0MXjjPQuuk1dFywgNgZPhuw\n6XVBsR8AULoRupQUeXeG9c8o9wOA4n5TOsbrDKzwbidmRtBxhBNtL3Cp2iNSZFzSHYm9e4PSkaBM\n2ogroVt6G3qNq0PB4b3o8Omn6PySyFjSpaSgzUU65PRzIbOLXzZ2S9+t7jebodMT20fKoAOIJk40\nkgeRZ1E3ZwCkjMiI3QfLq6/EPAfn6tUIHFZSy2lLjcracvClagXj61FwmziHeuvlLIDVQyj4OfPr\n/7F33uFVlGkb/82pOS31pPeeUAIICEjvvYNYEOyKYi+f7qrrrq69r666trWXVVnX3gsLKlhQVFAU\nUBEILQnpySnfH+/MmZnTkkCCwOa+rlxJZubMmTNn5p33uZ/7uR9vpO4HlbuY/+w2UiqbecMoTBWt\ncR4yrr8OU3IH7hcN0sbHkXXnHUgWMSd3lql+P4ZY4WVlNAnVWdoVf6R8/TpiSkuE6uWNy8IqCgun\n7tArD31e2LJK9102a/ygCqZUkjNqN7E5jWQMriJtcDPW1Dio2QK3lSHVbcOZ3kzq2ScGXhPtOawt\nZTDGxhK/YEHIJta4VmxHHBF5HxFQMHkHBbcvpXBaJSlHD9GtS7lE3E8+TbePuJkzsaTGBtR/AD6r\nifcrJIynHc/+Qulu01XIWDwEe4r+PbZeKLpfbTnnXN1nBbBkZwb+TjrzjJD9JZ5yShcc5cGDbiIh\nCsK1NlGMgoKhSAnj5sym8I3XKVv7NcXP3obNrV6MzvFi8lIwJ+wuMMUHsbXxkf0W2gPp1DfAltD2\nhm1AWwOa/6xaBxU7RHFM9lMwpZI4WWbrzGwkf+IurPyMISkr/E5zhpAxuIr4Qv0D2egOlRs5UlrC\nDtwmq18vN5SPtXimPtj0NBuwJFgwukW9ZNH7ov1lTM+emFNScJ8sBrbYATkUhJEfugYWk/WXC8gc\nLEiAounhZbfamkYFv36YRM1m9XsNJxWG6BLumISWsEEnwO6n1faASWW1pA2o1p2r5N6RA/RIpl1G\niy/QvUNBcP10/OxZkQfzt66geNZ2nIMEqdbw8UpKnruVnNG7dHLY1H5qhk5bH2yNayWhpE53PvMX\np5MzeldI5rt4ZiUGY/ja/mgPm9hc9ZpuHWbBZJWPq2ozsam7dQ9s5btJKK4Pud7cPerIWmDWObMX\nTN5B3ng182BPbsGg+U7cPeuQJHBlqiqKr2Y2cPYSI9uS4I75BrbHg1L1sy1RorluG3zzvNqBAgJm\narnjxDF9N7SEYy81UtijhuSFM8N+bu2kxuZugXRZ6p47BCx2sNiJz2+k/JitJBTXkzWmiYTC8Ndm\n4dRKMgZXhRAWBZN2UDJ3G9kj1YmhJdaDfcotvDbnNR6Y8AA2TcDkVtozlWnctKfcAvHZSH2PJXes\nPouTM2qXzpQOgEv0Rkc2k1oqluDIwNajnIJp1SSW1qnlAMmq4zsLniS27wniHBnFd7nVH77HvBZK\nJw+Dpu/9mOZbOLXlIvYk9FY3jM8l+ESZ5NKLf/tk80CrE5JL4I+RS2Qwi7FE6rMgIBN/xyGW/X37\nDu7Ypk7aMwZVkT9pR8jkM3vkbjKH7qF03nbsbn0m02AEo6Ex0J9eC8kAfBtZnm2Vs9+urCZi0h3E\n1LxPzOeq2a0tqTX6RDgSkoqQDDB4zkL8kqR21dih8WtprKJFXlwln9dYn5djPnuOER/djVMmiVrN\nEsvP/oZbRgp5dqXWL9TnC2nDbHZ4Mdt8AUl2WVCp1TqrhXUWMw2SRFJpPWZ3HOs3P8pxlxi5doDm\neZ5Y0PbnNJjAEeWaO/J0uFITbE27DY7W1yUnV9SK+n/NeGiN81B+bhLWWM1nO1mQWtZYL8UzdmBL\nDJPRlssytEgoaiBv3C6M1ujfo7dR3J+RnlthsVe9di1bV7X7ZY43JhC/+Y9wUz789zaQSzEC2PJ5\n+BcGQWnVqyXI04/UE/+O5Hr9uS0vx5yhVzwBpM4JSijJ15XBCNJ/zoFNH2H78R7Sj6wS79fahLuf\ngaTyUOLf51HHDeX5abL6yZ+wK6Aec/esJWtYVUjpWvZcN/mL0wLHXDB5RyBAql4m5g65Y3a1XUKm\ngaK0SVwYvgwn5ZzTSSqTWyRLhLTY1KLBKuHRTPmSetRy85LI2e9fkkP3lXzRhWG2jI6EpHVY0t2Y\n3OI5pPUdSV4iygpC1I8r7oJNorzH5m7RJazcc4diivGJMbmpRqg73v0zoFf7ZC8qh+2iy5g11os1\n1otkgLi8RqTV98HbV0FjkMq0pR73SccEVJeKUlCLgtdfo+idt8l59FEybr6ZrHvuxuh0kP/vZbqu\nJN4WA4knCIVF8ccrienZhpGQDKPFj/XTP2BxeknqY6DwCjVBaU1A7ZAgI+PGG5BMVt0jr9VuAUnC\nmB0hJmgHDGY/WcP2kHZE55ntBsNk8xLXw6ZLVoAoAdl25VXUvf9+6GtS1PmMKTHUY82UsP9x2MGM\nbiIhCqK1pQuGIlmSJAlLXh6S2Yypz2Tylv9E4VtvUvbtN8RNnw5X7MB62oNha7BNWXnE5TeQVF5L\n6ddfQYKoMQqWskWC2S1KHWxJLcTNmgE2MUtKmDcDyayOlO6lS0k9ZrDutQnHHYtz9GgK5No5gOwH\nhAQwdWbvgDzLmCYy9pLBT+aiARQv/4Dy22diPf910h55j6x77iZ7uDwQ2hMhtTcFU3aQN2EnaUM1\nnyM+h7i8RtIH1lAye1sgUG0pSuGaOSeTe7yeYAh+FiWVi4d9sGJDKV3UTgZa9prBaCbr9ttwjh6N\nKSWFktWryH3yCQCsQ8VAaxt7DAa7nYwbbyBjyWTS+ldTNHM7WedMx3X06RgShQTZ/MevSDzppMD+\nTWki8xhiuhUGhgiKhsyjNBMWWbFiT26mdP5W8sbv0nVwSNUMokaHCCwLJu8gpW8tCUUNFGqIDkOQ\nBFWrAoiRa3Pj8vWTiITielzZ+oeV2eElb7wIWJOGp8HVcWGv4ZSzT4bP/4kpxofNLEzC3KmrMb54\nLAajmu0xOz0405sDSgStQqBg8k7SjhBZewXWmB04UvX3Y1KPWp1CRJuRKZxWSUNlZAMwyehn3Z1P\ncfnQM6jOjNx9QJwPcX4SS+p02SFnZiPSX2ro3Xw917aqLLv17OcwXbyKxJJ6LC4PrkFlwtgrCNrv\ndFWKmZ3xEpUmE/UGA61miSVnGzn+YiO7YyValTyrrxWm3R54nbu8Dru7lVpJ4r3dX+M1Srh9Phh+\nISx+WQQeU28LK5k2GAFnUEcSsxr8SBK4Js8IIWni8hpIrtiLxeUN29rOYBIZUa0Kw+5ugdKpZLuy\nGZw+GKtRfDdJXq9a8aOdzR2purnb555P2RU9Kfv2G8rXfBrIenKsxgAxaIDQEgkOqwvOXI7prztI\nnTdQTbQO0mQOEnJxjRIqCckorv3t6IO6twY9QnxRvY6gUib5RoN6Hjb6M3jH11/f8aSHntj5aWcd\nLd4IE+agFrAcr3HejpGvVYMBYrP4zWTkmVgXU+rqGd7YhFPznkarP2yLSWd6M7HZUUqBvnwcrs/S\nfT6QT/GmyFLi/Ak71S48d/SGN/+AxdmCI62JvOOTwypkAojmDTBcuHvP3SKIg2vcifw1KUEY2V6T\nHMj87ZXbz77ldGDy+3H41HOh/RtPC7x1JckmB99naT6fyaR2eIkARdmgxdGZ6QzKy+bCFDezf3mB\n+zc8h8ckUaVthzv8IrisjS4P0RQJl2yEKTeDUaMSMFrFdRWrZsMkKYJhavDJd6VCr3kw7s9w7DPR\nj2sfkFQgnhVawu+N4j9Hf9F2NfudJe2KsmEY1Gok+suWBO33qw7tKja7kYSSOopmbo/YojUurxGb\nu5nse+6m6MG/kNq/mvhSL6U3TKF0/laMZsR1pkBLUH37Ijw6HYD4gkZB9n96H9SEb6Wr9b8KFol4\nW8S6hOJ6JCnUhNiw5iFirOo1G87Q05bcgqEDBF9rgwmz3cN/PV+EXZ+442r9guRQk+CP+zvYnurn\n3T4SLdrP5IeHqyqJiZBw8blCiSn3wnkk99mLM6OJhJK6EGVGRD+i+p0BRYOnXr3vYweVEz9rqhqs\nKoTl21fCo4LsNphEEqPkBB/FM7eTnKlpg7nxQ/jhzYD/i7ak1dH8rug6o8AYVOLZsEeXLACgdhvJ\npxxPziihuswevofSudsoeOyOwCaWrCzMaWk4Bh1J3PRpmOU5aUxZmc5/w2T3Ejt5MuXr12FKSCD3\nqSeJmy2UMSl9a8gatidQphURDbuxJMcGzrNv1e26jinxx8hKCPliLfzLHLynLeD/6h7HbrITS3Rv\ninDIHrGb8it6Ujp3G66sJt3cU4kFIsFx1JCo6zH4dUkryeCHL59AktAlQ0Bt4Rk3R58NdhSrZKJr\n3Ojo73cYoptIiIKOOG2mRGJFJQlLTg6SMqkwWSHnKHLvvYXsO68j9+mnAuZM2ffdT8bl55Dyh6sx\nWCxQIOpgk8pEkG1zt2C0ekMC1twxuyj74mMKHrmFpB615IzeRYbc8ggg7dobybhQBDqOAhfJS89G\ncukZsrSrriL73r9jLcgn+YILMNjtOIcPp3z9OswVIwJmahuViQoAACAASURBVMa4OIpuWEDRzEpo\nbcCUnAqTb4ScQRhSi3CNHSsmKMpndSRhvW03tj99SsLfNLLdglGifWb5dIxWfyBb0hrv5CtTb7xn\n6yW+khxcuyrSKJm7jZQ+tXiLhMIjf9IO0geKQNwnp3G158hk88LQ87APHEj2vX9HMhoxulwBcyZb\nz54UvP4aCYsXA0KWFbf0RhKKG/REhRIM2OJJPv88Uv9wOQank8ybb6LwjrNxDSgL+fqDoQ0eHWlN\nJBTVkz1KDFb2bHE8rjyJwqmVZM9wBLLtCgEhmXwkltQHJuzevar8nFPeAbNdd8ySAfLvv5a8F54n\nc6xHZVkNftw9anFmNJFcofcCcGY06QyzQBAStqRW8ifuIDldTCDCybkTd6qlLEmT+pB391W6oEUh\nLzwN4n5I7i3q7032MCUqmv1LU2+FvOGQP4LCmxZRtOyfpFToHyAZg6tJ7V9N2YKtWJxeEo6IDd6l\n/jOlpLAmuRjJEsVIVDJiTxZGYRaXNzAft7lbVMIMeNA7ld9OXQtzH4LCMZBUhMXlpXDqDszpGUhj\nrwjZdbwm0/9eQujDtcYp2iUCtGrnhwNOBoRQVZn+fC5fy2YlkDQYIX+ECDwGngKnva8LOALoPU//\nf1pv/f9l0wN/KmqajMHVuHsEZc7GhH4+LYlljfPoAuQYkzjerFRZEZGhkVvaghj9MX9EWvi8GENj\nYsEq17Nm9BVk6+ww3iEaMzRdRuxotU6YRL0ZVKxFXC+SaS9IoQFlvddI+oAackfvpt4vt/FVFAlS\naEbP50coEdL7ICILFWNv/ZB73g/fUkyHfidA8TiY86CYdPbRBNxnLmfnPOG4Pb0uSGrdL7RTQghO\neRtGyYqB4HMuw++NFv3rIRlCg1iDCXJG7cHmjRLMSQZoiVKCJRNM1m//HVj0TKzsD+QVpMD3L5yg\ne8mUunpdb2slFLP5fIIkWXkX//5pPa8e+05AEhw3Z44gJaIgQdNy9a5KvTrpbYedH41+VtrFde7U\nbIvdDVaNp9ExT4X5nKbIKsRwSgUlC6hc6/Mehswgs+fR8n3ZsAcsmvePy4F5D8Gw88V4tT84RtS2\nV/mdXNoqCMD4wgbRsURDvDbGhe8kEsB714Rd7O1oR6jgsohXLujQyyUjpB2xNyRJoYXJ6iNv3G7R\n/tjXSmJxA+n992CwGMTluuoBuFZDCq28O+K+AHjnT6HLYgWZ55cvyaQRmUjx2bpNUvtXE5vbEHhW\nKvOezGF7REkLwN4tQs2SLZJHugSAQcj3td5f7YGn2cB/m38I/J94XCWp/WowOzyhhGFyKYXT9CrO\nZTMTeeYYD3sdEq0mjeJCvl5yRu1mydlGqoNEus3am3rn93B1HPzwFu7yOrJH7BEJiKBW6YXTK0nq\nUUv2iKDSiTv7kDRrJI5BRxDv+oKimdvJn7QD047/kr6gn6q6+XsEr4HM/hhtJqFW2vGtuvzdP+vG\nMy2REXJuMoNKfJv3qp2+FOzaoF4EqPNBS4bakSRaN56Ynj3AbCauoJ6sYfoSUIPVSuofLid+9nTi\nCxpwZTVRdpqagEm/4XpS+6tJrn87HbzStBUkA01H1fPkKAOvuPdgconX2IcMJv3qq8XG8lzE8t3d\nHOt+gRZ/K0dlHEXi0NAWnAqSK/bi7rWXwmmqeWx8UT3OjGb4UfVb0T5ngv1axHo/7qNHk3X338i6\nO8q9J/kpnrmdjMHVAaVHq6aDkDO9maLplSFlRJLZRPK5grBMPaIG80dqi2Pzyj+R1r86cP8Z4zrP\n8P1gRTeREAWSNTxztqlAL1szOJ0BBrBdMBgwDZiJc+Js7P36kX7NNYIhdLthxMUwUHZsNZrhyl04\npwizOpPNS/GSDDKPqqJkzjYssa0k996LrV8FUkwshuIRpFTUhittxFooWGHXIFnOq5kv5dyhzxS4\nzzid0i80csCy6bh71lH21qMYYmIwj12CKaeHepzByJHVDtq7PalQKBQUmKww+z5IE+cyrqCBnNG7\naChMIcZsxJWYztqF57JmfAlPJyzhporrxG6mDcZo9tOU3BvjfNGuKCbeQ1x+A/GF9YEAWPvWOZfO\nbnNibc3PR9LKs4xmYcQGqtRs4l/hkp/A6sJgtZK4aBElq1dhHzgQy6SlcMZHpJ51LPETjiT/pX9T\n/PFKCt9+i5LVq0goqie5916MVj8pfWtEsD6ghrQBNTjTmqHvQpJOEEyuDzsWlxeDMw4KBLsZcORW\n2k0G3blGs18ELKP17RqZehsxI+Zg69mT2J5uzDYfRTO3UzJrO460FtFWy+Yj/cgq8ibspHTeVmxJ\nraGDs/wwjElQXYglCXInNepKPXQD/DfPYPv5n7rdmGJ8xBfUkyV7GkiSkM0FKycUlC3YKkiT3KFw\n4iuw+GUsMy7HXD4I5sjOuVNugUs3YUxMJ7G4IfCwTr5I9F+OHTmA0q+/ovyhJSQdlRI4jma59VWV\nozDsezP7frjwu5DFJbO3kTM6NGMWn5whAnOh5wSrTGQ010Gv0FIDa7yPtKF7+GRcC16jxNCG0Oz+\nqHoRoHqCZyCXbuKOov4ckZ9DK/CtVWQ2Xv91K2HhcId+lmEXEtKbcISmfviP20UQKyP71H4UTNFM\nCO2a4GbIOSFvGXINaYgERZEQY7bDeV+p3QzO+QKWttF2auELMPA0oaY4bw30Ca0F9coTr2GZQYaH\n2mDOqn/Am41mYowxWN3v4yz+K29fMAK/5nNV+VTC6eLWM2HG3fhkk1xjmDKhy19cy18KnhIkjgYe\nbzvk3sWCJA0YoFXMhyt26MdQeyL1LnE964LW4omQkNf2e2QfKcZhgITwAayiSMiZ2DEz07DoNTf8\n8v4nQa8I9X7papeJiFPlT+5ha5D51aK9oVmq+7fvYNlv2wIT9Vifn7Rt31L25qOUr1+H0ekAjzyJ\nT+0lfh+xKNK7MjrM/aqF7p51JOujiLKpcPlvoS9KyIXxQQH1whejvg+xcjbQYAKNEofZ90ORbOpX\nVwlxGkmx9llnssKSlbDgCZ3aCYCcdji/l02BK3YyuvlWnvNGzsZ5za6o5zMSjHISocqayVc+TYlI\nW6WfCRri4upQMz3mPCAIlf3BHb2hXg5Qfa0qERUcDH5wXcf3HSsUkEpyxGn+Sq9aSCwk8coHyRyi\nBnrJvWspnbeV2Kwmvfpg8wpIF3Ot1H57cRaK+z5DLt3wGfWku7aczJnZSNHM7TpDVb/XgCGjhSdH\nGVh8oZEvbVYSS+spmq5R7CjEVVIxFqeXginquuzGagbKRsqtmkeQkmgwmv3sjpW49BQjr81vIXaM\nILj3asVa9xwpfi87XXfs2rE4cfEiTDE+UipqsaeEqhxMT40nJ/8VTDE+zDa5NOGD6+G7l/QbhiMY\n92wEUxjT6N0/6qQjUZVYDrf+/83L4csn9Mt+elf9rBpID44h7bILyLzj9pB1VP8KtaJEzuhyUb72\nazKOrAlLjhldLtKt92vKztTndtymK0ksVknyK5OTuNzSwF2169jpNPDSEAPXJydiaRLlGpK3VfUo\nkdVd2lnA9MLpGLcup2zBVrJH7tYph8vXr8Pdo47kXnVYnMI8NnfMrohlDCa59CSY7M6btIeyo7eR\nbHgS17hxISRL7NSpFE4V8xh7SkugrNWZFj5xbHZ4Q1Qt0i8rcO+4kvJjtpJYUo/J6iM2t4G8eRb4\n5gUSihuEj8fgKvJu6RiReSiim0iIAnNqCsnnnx+y/JesEiSbDWNSEpbCQko/W911B2E0Yz7+bvLP\n6kX69bcgnfkB0p9rMC79gMIpO3Ff/yjSae+qE4PyGWEf1tYRcyh++hbi//ggAN5GMajGFzfjmHR0\n9GNIKUP6cw1SjjyYuVJhyYrIk9UUucd2diiTa8pIJ+F4jdlKkxz4S+BIbaEFE1aT+CxHX7GET4Ze\nzd8axrM5vYhrLnoE2xHCPCimabeoKZ56G6T3RTJA+sCagLJBmqQ+uC3WfTM4JL2P+C0PyEJ6qh/4\ng+v/Es+9ivS7HiWmtBRTQgKW7GyMLhdpT67EfZPI3CSVCdMrXZ33rHswD5oFgHXwJDj+eTj2aVj0\nbzjrk7Csqw5HLBYPtcFL4MRXyX7gAXIff0xkowORtSCTzLZQs6v4Kx7DNnRy4PknSZB+ZBXpgwSJ\n4gjzEAawV5RjdkTJ4v0a2rIy/ciakEFbitCmLCDVDZZ7A1QcLQwCjzxNBFhpvdR1zlSM/edS8Oor\npN9+v1D4DD2X5H+8S/ZcIblt9oiH6uqckzm15SKmNQcZg/aaC64ggtAai9HqD4m/AeyWoIXz/yl+\n+31I5lBSco+7hInD3Nw20E66x8O9lTt5OG4gFp+fx4sXs9Y9kVNqhFqkNXg2Yk/k+VYxMXvF6eBf\nLidFcYWkjv1LdJn46R8CEFOQIQwAg2EwwlVVomZfOedLP4czPsJ40vNYYzXf9TFPw5n/hSt36TPu\nucNg1n0ackj+rZFxGuUT6Pf7xThikVNPSYXR68QBsgfC1FuiztBO630aD0x4gHvH3Ru68ozlgkRJ\nCzXGjZXJH8nYxNtbn0GaeC17ksW4t9OvBiPf+PPgiBMCiSKDO5NVhj6869VnWx5e+XMIWdPkaQeR\nUK74RWjuizCft6pZ3J9OrXR/yk2QP7Lt9wChepOMMPH6sKsDpRu2cBd82x4SOiQHKbaGXyyI0uEX\n6kmGo84V19/VNXDGh5A1MGRXDp+PXQYDH9hsfG61cn6KGJfP9Do4s6qG0pZQRclRjU1keoLGqifm\nID0gB7+/fAJ75eA+U1bItGoIlKyBOmIDINkTXvqe4vHws9mkfnvKNb3oP4F7EK0Sata94JTlsYPO\nUJUFyeUqGaAg2GRRIcmtLn1pRp9j1PvS16p+X+H8GlJ7Qvl0oXY6VXgIMWQpLA7q8pEhX99KqVRv\nee5gslBWED6wb+p/BhObb6DOmQ/T74JZ98FlmoC4z7FhXxeMX6c9zU9+mTSpOCaEoNNJwtP7iLEp\nGsz2iOUEHcL3ajkonz20//tTfK2MFjj3y0BZaoin0XHPCkJKuR5OfhNJkmPY4ISCJEGJICcNacWk\n9fiZtIHVxA4uhgGnkH2VWuZVOm+bzsspc0g1ZpsPw5936doe7rIY2NSvlQSDl0tS3Gw0m9AdYZJM\n0MuDpCfOy5UnGHlwgoH5lb9wcs1e/vXbNi5rVpU9zgz9vKDaKSG5PWScPJ03j2miytW2OkVRb9qS\nWkid1TswbCrBoLZlbkRsCGp7+eGN+v8T8kWCac/G8K+v2qT+He2QSyeHLlulUdjlj4CNH0R8eULj\no8TW/Uu/8NWL4Y5ecGtoSUkAr1wIT0e476o248xsxBLbiqS5P+o0z58H6r7Xfdc1SeK/+lWfw0Pj\nofK7gHHtLtlU+NTepzImZwz4hQrGmd6Mu1ctNnczuRODiF9Z1WxPaYnYEUrxE/HJREJMUgul87di\ni9eT3pLZTO4/Hwx0ubIUFmB2ekkbUE3mEDlJaHZE7BAF+gRZ1uWLSU7/LGR95pBqbKbNuuVxeY1Y\n3g9NshxuaKsa5n8eRo1Jxt0Vs1n69TJiq3ZQ9mX4+rCuQsy5QYNFRl+4YmcoI7ogtKesAlM/1XTF\nVy8GbHNMF7if5g2F874Om+Uqfu89/YI+x4oB2e+Hr57C4/MRo/Fz6JkRy0trtmIxGchOtKuBnTKo\nDTxFlBzcHJRVtqt179JuvRFbu6FkNMJJPDqKuCx9tkiLsULWaC0tI++5Z4kpKwOL5ntNKcdw5CJY\n/qp4KPU/SfhfPKOpEVeCQoMR8obhzAvzPtPvFMFT3+Ohdiv8Y5S6rmSC+Lm9t5hcDTyN+JPmwiOT\niM+PknnzeeBP1RSdsR1u79GOExEeYRUJMfHQVK1+rnCwaLSPY66EXT/AyW8GJmPWQv11IZlM/HLq\nOyy+/wPOkAO65Dgnj/uCJMEQIkcHRKZSblkXPFkLMZVSjlmSwhIhI50NKFzuGVU1SMDAGQ/weWuj\nIMn8fkxfCSl+uHCl1J7O6qbtXJUsAoTTSudDeRuOyBl9Kf1qjVDfRArEg4yTcBepf5/6Hnz5GHz+\nT5EJDZLaGq1eoRyRJKRN6+HV5wQJVj5D936SPLvy0wZBto+wm+0MTh8cfmV6RSA7Fwyn2ckOBEFz\n79d3cVa/0/h6+P3c8/Qydm2oR2nS1ugXxJDRLuFt8GNo+IU/Ji5jw462u6Q0tbajlVacfF7dJVE3\n+2z7ZzjNTvIu3w7LbxMT27hsQc7kDIFf5FZti/4D1b/AhzeJ+7tUfhZk9IOrdovvxp4EDUEGUzKR\nYAgmyc5eJVowhpNkR4Ky75g4WLhMBOvaa/DEV8HiFM82LRLl8hVN5rGopZUbkxJ4w6kvSzpu3K0k\ntLaIDidDlsJtGvKicKzI7oVD5Xfw8ET1/6POhZ0/QP/FsPY5sexU0TXlsnVPsmr9i8AvLPttG7+a\nzBybKZ5LJ1bv5Z/xscypree+hDi2moyCvLDLBHSBhuCRJKGsKZkIxePV5SYrnPqukPr3Cio9AtFp\nZLaGIBtwsiA5UnvBO1eLZTPkbifarL09QSh+grOgwcg8QgTpGf3EMcZmCoLlvK+FIeIjk8T93Hu+\nqtwArp3Vi3G3fcQOfzwpkhi3q1OOxDP6Gr5f8Q4Gg6zU6isHMOd8Icb3zP7wwxshJnOewvEsWjeQ\npywiKVDRq4JvnpXHZItdkDMDTlGD94l/Fefr5gJREhSOfNbCFCNINL/+fvT6pYAKol347t9tb9Ne\nXF0j2lO+fol4/iQWkLF0Nnuff1woDHKHwc8yQeIuFr9n3wsz7xHj9tVy9raxSnidVMuBoMUJRePg\n0k3wzQuYd10sTHTzhsOk6zBu+ojYnAb2/mIPlBfE5jQQm9so/s8fCUYTsTlN1G1roCHexxcx8Uys\nq+frGKFumJmVwZKqGmbV1fGPuDj+eORpmD+4Afoej/+/tzMmJ5MGg8T3WRKX/NKCAShraQVa2VFe\nS8xxf4Zv1RLh4/bW8VSsE4vfj/TKUuqSEvC1zSNgMIm2iTGJrfDs8WKO+dXTSK4UShbUYPC3syOI\n0SJKpyCUSEgq1JMFwfjmBUFULVmBdJcg32xZmrmK0SrGk/QKoVZ6Msx9nt4HRl4W1ZeGym/Ez+Sb\nwBwDLfWw+gF1fWN1wCtNB+Weaa4Tc40gZA0LMnwsmcSmzfq5e7Nm7K51+XGB8Pfa+gXcOyRAcG6U\nFQFHpoVRVUiQN05+LmjNc3OPEubSUaAk13weidJ5W8OW1imw/3QHZDaTM2YX9tNPR7r2chKKNOWI\nuUPgx3fIGFSFtzX0IguQUEPycG26HtrXvVzA1yrim6jSlEMbbSoSJEl6WJKkHZIkfaNZdrUkSb9J\nkrRG/pnStYf5+yF+7hxsA/qT/sxzrEkTk5Lvc3q18aoDhHCyqnbCWyse9MaOuCp3BBGksiFI6yUm\nRini3Pq8Piwm9bIsTRMZws27GzBIkqp2mHKzug+HO8S9WtIQCbpgsyMoHi+knmOvbHvb9sCRJGT4\nCs77Wjz4h6sPT1tFBZIl9HuV7IoM2w/T74BxV2PRZofN7fiMMXHivVypamYJ4A8aOfw5nwkJ9dRb\nxPbhkD9STLQDBydhTk/HbG/jWlLk62GgPAB0JkvhAvloSK8QMnlXmirZDgODzcVO4gOKhBSXuu3b\n3jCtkcZcKT7zFTv1D4PMI/DKmeDzxxWHvi53qJjQTr9Tfzy956uBnIyZgy8RWTaDUX2wSxI2uf55\ng8UsAkTZeA6gKkY/ATimNIoSQQOD1Rq1pjIqsvrDtDvggm9DSISS2dsomrYjcI6kTKHoMRj9+usN\nlUjQehkcDFBKLrTwW52s9pexaZc6AW1AbJc9IwF3L2E8ed8JYcioMGhsaQeRUDgaTnxNf5+FwSfb\nPmFg2kBMBhOMvFSUiykE1uKX4eINQlFSMBKOOAGWrhIB9hxN1ku5pi8Nza4pcmCjM0hR40iGn1eG\nHlBsppDIm8KUBRotsORjuOh7cR0FT6zyhoWSCIHXiuv14t1VWH0+6gxS2ESf0xInzt3Evwpp+CQ5\nAHCliwxusLmogrUaol4yiCDtlDfFMZ2xHM5cEVh9fPnx3DlJKPvifH56XbSJoQ6RoT+37Hi+2PQL\nQ7MFYfCT2SzGjkg+LFNv0ZMIgWOQBDmcGoacDTchTestlisGf8rYHRMLWfIEvqlGBECRxnXt/rUk\nzxnLhf9OQq6YcB/3nBgTM/rqzB+LUlxcMrGU4c138LpXqEg2xw/GJ4+RhhDH5EJVeZFURDBaZv6D\nlb5eTGu9QRiOShKzBsrEsPK8m3ab+oKYOPGMvXK3KLs0GAPdKcLCHCOedSnCub5l7mOUNT3C4Oa7\n+WbGa+L+O/lNQZ4OOlOchwMBZV5nEeO7OSmOpDJhphiujAsIJX9tCXD+WvV/pYzLnggpmm41SpDp\nLiVjcDUlc9XyhcyjqnFlyommQrVkJWNQNX8aJUiaiuaWQPkdwAsuB390J/FCrJM1JuCCb8BdzJbj\nn6FBPsaLdleRFmQ0m9KnltgBQaSpUmMv/zb4dRW5UeFMb8ZklZ8tVZvF7/odGKX6iMFmCByh3TgC\naKt0bPtacc7lfRROrSRnqiYh1fdYlcwuHh9qughwwr8hq51t0p+aD9dlwCNBCofv/g11ei8XPr1f\n/furp0N2tdcgMTMrnVU2zbNwwZPsNepPnJZI2J3jJW7SKAqnakpb5BKHn+S5RqErF3b9CG+F+ikB\n8Jim/DNYCRoGzgyhPEgobMBgikAiKKWBG8Q44EhpQfLLaRltR7uKY2D6XcTd9B6Jc6cRCWbnPpIB\nYc7z4YT23FL/BCaFWX673+/vK/+8Fmb9YQHJZCLviSeI79ubFXct4rqLH+argo73YT3Y4B6bR2xO\nA3FzIzyYDjTkgKLFJ+kUCXE2NeAxGiTx4Lu6Rkj6tAjK9ktOzSBh0ddCtxuSJLI91n18fTho3Ojb\nTbaA8EsIQuE8D/mTdoi69bayL9GgneSarGrQGyzHN5hFRuP4f8GEa0TAMO/h8PsMNv066XUxKb9K\nZrr7LoQ/6UtOCqeKvsoBlEyCxEK9O38nQGm7V90gl/fYzUzvIySzD3vDSA1HXCwkviaL+NwpPUTp\nSdE46prFQ8lpDaNaMZph5t38Zjbz4PqniC+qJ2NwFcx9EP8xTwY2u6tyJ6ZhF8Cc+0N2kXm8qNV8\n3uWEMz6iZti5bKzeyLINy9hSK/p5ZzgyeP/o9wPlAl0OSdLXW8swWv26riSGuHiQ/KT026vPxAKZ\nLmH8OCprVJceakfRXoVEo5ySsGXZSe4l2nkWJodmdgAaWvR6kuZgeX0k5A0NDRA0qKyv5Le63xiU\nHsEMzGgWcnmtosRsE0F2mCxUOKQd1ULhBf0xJmcKk8tjnxH3tjUWBp+p3/iYp4WBY/l0+L/NoTsb\nfqEIjPdlrJK9CxbvrWV2XT3bLTakstAJnzk1qJ3ZkafDgifhgu/E+fBG6MpQs0X9O5jcSq/Ql02B\nmISe9zWc9AZYndw+63lem/Ma5onXYV76GRaZ8PNYXWLsOFDZKKU236qpeR8tG2q27qPPhSNJlBMp\nKJkY+myQUd/soRkLXtnessng5J11sumYIco5mKzJ+J7xEYy+ApsrgfPHFXPHeQsDXi12g3wvKb4Q\nWiif2WhSz3cwETNXU3pgMIltl6yAJR/jL59GE1Z2kkBujyPF/ZczWJBek28U18GF6+G4f4UvHcpp\nwx0+4me/Sf+/0uJHmXdoSzYUgi53aPv2fbSsUNV6RKVozkn/E8VvVyqSAV0XJB3ktoec8wX0OZbB\nbuFZsKC2llt2qn4KO+SuQwA2izrGfGlQ77vjtP4l52iUvUG+BF/HiDG2oFX2TcCPrz33UXDnE0WV\n1RYW/QdO0LS3jcY4OCMEusM09fAWpxhnz1whPK/qf1bXBX9/itmtK12zLEHMxbRGxiMvC/++v8me\nZsHq25fPg1uK1IAa4PVL1b9/fFcYsWpwQUoymyxmTk1PZaVNvt6MJp6WDW4nyca+dZpnU43FQMb5\nC/XlunKZ1c9mM3afj+QHxsMDY8ATYRyq07Q9trtDy3MUyKSj2e6j/Bjh6aUe/Lf6bX1evdIB4K+p\n4t7XloAnFQr1WWoPGHJWyFuqZuBtzA/yhodf3oaJ76GONokEv9//EbCnre3+V2AxmWhtj1nWQQ7z\npEvJPGcWhmn7YALUFZBvtLoWH6mxKhPqtKrBUdSJSFAG2piqyZZOvqFzjrGzENvxPrqSQ55UaE9B\nw25i4j2ibn1fJqoLX4B5j0ReH58Hg5aIbAyIjKc9UT3X5dP1WWmlXnbAyUL6qoUyeTEYRBZoxt/E\nMV+4TtRnn/8NFpdXTGSSywUbP/NuOPcLKA3HY+47zEZxrv7z1VYMEvTNTuDW+SJ73uwXk7Yd/vhA\nJk2HzP5w1seBLGJ9NCJBxtJ3l3LnmruRBtUF2iU2esRvsx9G5YchL2TE5A1jQu4EqmxxXLr6BoY9\nM4yZL83kqpVX0eRt4rTep/Gf2f/BbWtDrvw7wGB3Ub5gmyiNSeujW5fpzOSjBR+xuOfi3+nowmP9\nnvWhC8NcBv4O2AttrdZPnBpbOuf58WutaCeY35Yb/r7grE9g3sMYfA1Ytr0MP6+AzH6ipve090QA\nlhSkwimbAnFyZxAtWTBkqbjPtRmgjqIyIIikcPwN1OPlx/owZoUh5UUG4TehTHojTei+1RgaBqnb\nIkLJ0CPajWa7lHKUYoxywOedemv79tVZCCgSNESCtua+i3HWaDHJtyKOo8Fg4w/LRGY82uObzP6i\nM8nIy2RJ9yVIksT540ooStEQ+fVy0BouY6n9zAqsLqHKUTpTaJV7StAmSZDaA6Pm2nHFRFBsxaaL\nEsC+x4Wus4Z5/0lBc4+es4WxpRbJZeIZeIYsYW+VM/xKIK49b85UoYxb/HL44wtGjxlw1R7oOUtd\nZk8U+/hTterLAYKwn3wzjPw/WBRkNmiLp6a5hobY5k4YDAAAIABJREFUdJh9HwbZhNPiB2vucGbV\nqiVdNfK9ZtCokm77TChHTu15EhbZQJqicaqPAoQEmEfvFfsc3tgYOA0+iyPU+2LG3cKQVFHalEwM\n9b/RBnhylxEy+olrQ0HBSH0HE1+YgsLzvxHfn/Z8asfB4ReJchtQEzSKItbTKLo0LFkpVIlanPy6\nKE/RHqdyPWoNkHM05Xo9Z4ceXyS8HUFV+8PrcJP6/PACq2zq9/aDRrn4odyNJl429n0iVr0v9xoM\nouOEFt+8gAd4Ks5FVqsHae8WaA5vnBiC+Bwx31z6uX65xaV6vYT7/MEJDl8rrLgjdDufR5SXKNBe\nh2ESjwpZ0bw9SqvJ/ifpiUoFWQOFGvAwxv6YLS6VJOlrufQh4gxBkqTTJUn6TJKkz3bu3Blps0MG\nZqPhsCAScCYLyfW+yv47GzJjuqvBQ1aCekwOTYBmjBYsayeup72HZNdckoox1MGCJSv0THw7YHCG\nqXPrGcHpvL0oGhfZLR3E5HvyDTDhWtFvvA2ZNeOuFoPwwFP12w44WV+nZ7KqE/vYDMEAaye5Z3yo\nk1J2NkyyRK9ybzNjy1NJi4vBYjLwwpIhNMmZZi8GdteHN5jUIqBIiIlMJPxYLbIErzrttAJnvn0m\ng54SWeSrh/8VaX4UMgdRW1jvaeD1za+HrJtWMC2sHP+ggJbcM4aen4SYhFBfiUMNctaledyfaWht\nCLvJ1mq9x8gLX2wJu11H0eAR7+cyd0F7qaTi0C4LiUE+NEqAmj9CNejTYtZ9gqyc+NfwGeSOoFxt\nQ1oQJ8wCf6j6QbfJCzNeaHs/ihnhxOvAlaGSpNqgwb7/pJxJ9tXxRimx6hIoioQYzXibViECnFl/\n7/K3d1pNWEwGYmQioc6vPpdDShuCUTEfRl8efRslexruOwoXyIMIlpXvVzvfCVIEKokKVxRSOIBg\n36Ses0PL6SSjMD9e8rEIHhe/AnMfFsaWSmZ5xt0igB1ylmru3CwHK0ogqkjTMweIbU2WyJ5BYY81\nzLYmSyjpVjoJBp0uFCzpeuKXCdcy7JlhHPeqIFBaDUZMfr/gOOb/k6sqzmKQXAO/1SzOzUM/i+fV\nW5vfYnfTbuKt8Zw34EI1qFKe+RNkk+OGPYAkykmA2XX1rM07AaULo9Evl8K5g0wEe88XhqQX/SCC\nubF/Ej49Sz9Xs9oVGkPxsiminPPUd/VESjB8HlEaNVJ2xhl8tkicpPYUpU+KKfHZn8rjSbogrpS5\nTjhFiTNVvD743CcWCNXIiItF0iVSGY3SwtmeJFqotxcr/9auzfYGKeC2abrhTEoQqqysVnEvbbKI\nzxXj87HcbmPR2rt0xMM7dhtnponzmxPBlDYsSqcEOpbgLhIGrQqWrhb+CRDZ7Pc4TZna549GLiuI\niRP35LAL9eVeWrXepBtAMuJIkT3lXGFC5jFXCAJoyi2ibPgP2/TrB4cqHA437KuL3L3ANYhczTXA\nrcDJ4Tb0+/3/AP4BMGDAgK5x1jqAMJsMeLyH/Mc4+CAbHvkwsKVKnZDbLRoioT2KhOSygKw+pW+N\nTmp90MAWH94AJwokhxjodGdg3sP6TFpXwWgW/cbbQlwm/EETJE29FV69iOi2xTK0fh9dPPk2a66j\nfLda1lGU4tIRCZsqa0l2RT+W3XViwhwblMG69pNryY3NZU6xStTckZiA0Q8rtqr11uEMiIIRE67e\nXEZBfBgH9oMFUY77YMWxZcfy9PoO1DPKUvmZv/yL3356CAhVPwUTCf9cuVn3/7CijgWuD659kMK4\nQjxyrae1K+4XhfjJHgS/fir+DjZ+tDrFRDqSkZRiqtcZ0GTiUh2hPgfjc8dTkhDdmBJQSxvcpXDR\nOvD5YNUDesO9TrhujbI83es/wJJWT5jSBoMhfIeWLkKLx0eMRYyLVV712oz6/G4vsgcKs9twnSei\nKV6Usg6TTRDbP70fsokkSbx9wQgyE9pRehOs7nCmhpIL560Rv8P5XIy8VAS0wQG7OBDxW5HoJ8vX\n9Yy7QrftKmjvgcu30CqXsvxU8xOt3lZ2NOzAjFz66XBjHnEJM396mU+3rwq87K1fBbl4yUcio/7g\nhAflNfLnU86h4o/x/aviO9SWRWquYwN+vH6fmCtcXQMvngFfP6N6KZljhH+Ugpg4kc1P7yuSJp89\nIowAQV/OefTjet8IBY171PKtkZeFVzuBIGqGnC1+QM10K8kt7bWyuQ2fjeRSoXiMhIQ8YRo79Fyh\nbFWIhb1h1Fn7gGo5yTKhrp61MVa2mVQSqtYeR09DT4yN60DTs6HJYGBNjBXqt3BeqpvLd1cxorGJ\nC1LVEpNrdupNfKMimBDsv1i0r80fKQiG0VeI77NmC6x+UN3uFGGGS8kEddmbf4j8PillkD9c/Gih\nKclh8BI4YhGW6zIo+MvRmGs/h1/ldcMuFHPVYRfpVSNasvLSTfqWzYcp9kmR4Pf7K/1+v9fv9/uA\nB4C2Z8OHCcxGiZbDQZFwsEGWnHr9BgbkqjeeQ+MW7vNHIQWUukJNXVtSWb1wJj4MoHgkWOM0E1NJ\nEiz82V3YfnR/oJh8lbSjNOEAyG4VmDSmQVaNsafdYsQrD4lev4H10WRsMh76r3BuLktTs8KfbPuE\nZ79/lptW38TuRv0D9NYkdbJ7Uf+LSHO0bSoUTnFwVp+zeHd+BAf6gwVKgCsdIO+GTkC6Iz1kWTjf\nhBmyp4YSmP7WKmSd4YKljbuiu4Q/cWoEj4MIuPOLOzn3/XNpkqXAXapI0QY62jp5LQ6UqmTaHXDm\nCuIsoX4xdlM7lXWKIkHJOhkMIa79JO5/qYjiV3LAiQQlW9eZvj4dREZcDFbEed68V702OoVIGHMl\nnPtliNErEJ1ImHqLyOCm9xEGykqQH4TiVJcueRERyvNKec/yGUK1p+DqmuhKSIMxPIkAopxw5GWq\nn1L/k+HiH0Um+0BBGVNis8Dq4oNfPwisOuf9c3h548s0SohzKSMcKV7XUhcw1C1NlJUESicE5fmg\nJWD8PkEMKJ4BRhMc85T402AS7YIVzLwbLtkYXZ0hSSKwNBiE0kFrLK2gxwy1AwbA+GvEb61KKVqX\no2AoxIZyjWhNo/eX9DVZ4IQXxbXsLoILvwstI42GlCjX0Mx7ODNfmJ7PllwUWJOoNBkDBuG1zbXE\nWmKpyVG/Z5fFRY5ZDfy3mM2cnZbCNqP+O3H6/aGKNrtbVXtoUbstdNnISyFHfk4aTcJvS4E1Doon\n6AmoIUvFb+34WxHkB5cShuADlWQaIXtJyPeC9bs7MPwmtzOffieM+xOMuiyqj9H/AokA+0gkSJKk\nnW3NBr6JtO3hBsvhUtpwsEF+2HgxMK+/WuekDfpWb45i1aEYZLXbkvfQgiEuieyRu8kaE9RezpWq\nZiwONqRXwJW79AxxJBxQIkGdEJg115fZaGDBcGEi9Q4Dqaxt25zsnXWVAKTEqhmc6z+9PvD3niZx\nzd41+i5MkjphunH4jZzY68R2He/2etWE6MbhN/L1oq9Z0ncJKfYossyDAQHTzoOkfKodCO4FsKtx\nFxtq1KDjqKa7GNt8M26n/Nm8+vKXN88fzh+n6LNb3/zWzrrQNrCnaQ/PrleNR5tlGXunEgnDL9YH\nOFrjwWAD1QONASdBWi9cmhpWRYVQGF8Y6VXhYQljNtljFlz2S6dM/pR73XugTbbmPSxk9BHMEA8E\nXlo6jKIE8fl/qlaDsaiJgPZCbokYFpE6Y4C4phe91HnnRQkyswcL0iBvqAhwjntOlCvsDyx2UeIR\nCLQNohT1AODJdU9SWV8p3vOEZaLMELjwA7Wz1IrfVoR9baJNf98UJxTz6kbRqWlMtsZ7QFHNKAG2\nlghQstGN8lzPZBPG2ud+CX0X4vF7eHLdk+rrHRHk7TKqmqo4850z2dW4SwTh0a4RBUPPFeNDcODZ\nXihKBOVzaYkSbbexzoK7OPzycPfJya+rSpdgAsKRwlaZEI+f8zD2rCNpTukRILSqmquIt8az06e2\njD+779m8VHQiazb9otvVhJxM/b77LRRknoJjnhIdwoYsFUq3k15XPQ/qKqN/3mCUTBQG4NqAfuyf\noHiifrthF+r/d4UmDQBBGF1dA2PkshhtWaavFcqmqSal3QDa1/7xaeBjoFSSpC2SJJ0C3CRJ0lpJ\nkr4GRgMXRN3JYQThkXAQyuUPdWhKG2zBPctlBMvHdVDYf0VepiCmYyUEBy3MDtHSKOYQqylvbwvH\nYFloF8IchUE+a8qRcOF67jcvorapfXV92YmqFLbV28rGGrWN3p1f3AlAsj2ZJJuY9PxtzN+YUtD+\njrlaH4EMZ8ah4yugfKexER7YByG06gOjZGTGshncvf5iFCnnVtz85M9kZGn4iX1RiouFg/W111uq\nGsNu21HcvPpmrv302sD/9a1C6RBj7MSgceyVqukbQIus6JrcBRPgfYTRYAwQCE9OeZJnpj7DiT1P\n7NhOwnWtmHZ7260R2wmDTGgr5SfR0Oxt5rFvH8MTztyto7A4DmzmOgySXVbskiDYNteo99Ou2rY9\nZ/YLB3JcVHwMgg0eSyYessZqe5r2cMOqGxj3/DiR+S8cAw43n1d+3vaLAbPBzIRcNWkwMHVgYLy6\nZZQmiCweLwiCI88Q/2uf/cHBr+KNkljAT62CkL1hVfvNs1/c8CIrflvBI99E9yEKweVb9C1yOwKF\nDFGIM22SpCMGiVrM/DscdU6E99Oojy76XrRKdaTAqDCy/pg4YaR72nt6AmLOA7TkjwAgzZFGj9R+\nmA1mWmUFV6u3la11W8lyZbHTK55n19V6Ob78eEzWWIzAwobw49f5R5wvjCS1ppRlU4WaJyZW9T1Q\nCLj99f4CQRppjSlBlI0oCpr0vvs+XkTz1VAw7Y6AkuZ/AW3O3v1+f7hCxzDWlP8bMBklWj3dioT9\nxec/V9EvOx6DIneU+8x/68/Vyc21SHJGyVorbSG1uPy3w0ehoLDcwa2NDhcog/q+tursALSKhLBZ\nsth0HLbvqWuDSNi4U6hD5vRTFTRvbH5Dt81nlZ8BkGpPxS5n5pNtHfsOF5Qu4JbPxESsPaUQvxsW\nv6wn7hxu4UauMco71FDbKgIGyVSL3xNHz4xYlp01FIsyRoWRqmrnJ1kJNrZWN+L1+fdL2r27cTf/\n/U3vVv7Vzq+ALvJIUNCiBEydE2B3Fv456Z/sadpDjCmGnu59CJy144zZLpzyO1GGGiht8Hm57bPb\n6JfSj9E5qoGs3+8PEIIPrX2Ie7+6l1hrLLOKZoXd3yGH+Y/w47K/smWLOtbVt3QCURIOC56EXT+0\nvV2nQn5uRMpqHoJo0airttRuITs2G5/fx4lvnAiI59CaHWv4vup7Xp71MnlxeSH7OLvf2bz181sA\n7GxUzdXNWsPB2Ay4QtPqTztHC3h5SIBfR9QoQS2I+6o97Y5j5aC+pr3dAgLHtB+klHLMihqpvcmU\naOh3fOR1ip9FyWTRzcSVBpdsEMqPn44VXgKbl6utKR1u8ROfB8vlrjIlE6n1CGL6pJ4nYZAMWIwW\nWnzimvi17le8fi/5cflMMCZQ/clXjGmRP5d8rv6vcitzzGbmZKn3RII1gZN6nSS/bxvzHqsT/ljZ\n/vIPpbxhQFh7PtgY5IOitHMvn9nxDkInvQGPTIr+floMOKlj+z/EcZhEWQcOFqOB5u7Shv3CRz/s\nZO69K3ns483qwh4zuafPi6w2HhEx4zowr4MTPavz4OlKsb+IiRVZwcX/+b2PpOtw7LNw1sq2t9tP\nmAxaIiH8NlaTgWZPZFny8g07GXOrkH1aNMRXZYOQ5V01RG9ulmxP5tqh1zIme0z7TOE0iDHF8PTU\np3l00qMHN5GQP0KUs2gx5Kzw9cyHALT17UWpYrJmNRl033fwpMfj8+jmoLlJdjw+P394cS276lRJ\nqNkoMaFHKuN7hBoHhsNxrx5HdXO1btnbP78tjqkrPRJaZH+Hg4xIcFlc5Mbmtr1hJGgVCUs/g9M/\n3P+D0kApbVi3Zx2PfPsI/7dcrQWuaa6h4rEKlm0QPeuVri7+zpD+HyzI7M/H/W/Dp5liNndVAqZ8\nGgy/sO3tOhO954ugd9RlB/Z9uxDaQH3KMqGYU1RPAEMyhvD4lMf5cMGHYUkEgGxXNiOyRGZ7U43w\nDypOiCC9V6CMMUXjIGuA+Pv/NgmjOg2MGq8dLUkR7bMoBMY3u77huk+vOzClRgppojw/OtJhY1+g\nlJ8Fl22YrDD7PtHB4uoa0VVLC0dSIIGHZKSuVSRGlNIxs8FMq+wB9J8fxbwzJzaHssRSntxWiUN5\n0LWo5bZFra1cqzFWfHzK4wF1VrvKiswx7Sdx4rLE55Jb8IYgkjeTIym6r0E4aN8jrXfHXvs/gG4i\noYOwmo20eHzkXfYq97z/4+99OIccWjw+Fj0snH2/r6zj1z0N1DSIwWq7lEqMOfSSfPP8Efxpeg8u\nHH+QegEcKAw6Xbj2Hq4onXRAWnWK/uTy5CbC5N1sNNASZeL71a9qUGeRfRbW7FgTKGWYVzyPc/oJ\nKaLCyFckV3DnmDsx70OGope7F0ekHtHh13Wjc5CbJIJ1S7BaKiiIX79nPR5fK+aEjwEfOYlicvfs\nZ79y8b++CgSLS0YW8o9FA3hg0YA23/u1ja+xtV5vEhZnVQN7Q1eqrprlSeJBRiTsN7QEUFwmZPTt\n3N3Lcu3XNr4GQHmi6puheJ785eO/ALBKdrrfl3HhYEacXa8gbG49jBIwRrNoqWluR4eHQwRaIgHg\nxDdO5MsdXwIwOW8yo7JGYTPZSIyJnNAxG8zcM/YeCuIKAgTZKb1Oif7GjVXit1bNZksIUQgNyVCD\nuW31YQz5ZCzbsIwjHj+COf+Zw5UrrgREt4mn1z/NlrrOab0bFQpxoCUtxlwJp4V2CukUFI0VaoSh\nbbTnDofjn+fX2fdw9Fsnc9EHFwHgMItnllaR8NA3QoSeak8NvebjVUJXAmbW1fOkexQvz3o5lOyd\n/Q+15W5XY4qmnGbmPQfmPf9HceAKkw8TaLsI3Pzm95w9WrSuWbdtLzWNrQwuiG7+8r+ObTVqvbDR\nAMNvep/sRBvLLx1DY6sXmzmURSxNc1Ga9vu5UHfj8IPS0zySIsFiMkTtztKkmRQrweUJr6u1sZIk\ncXrF6YzJHnNwt2jsRruQnxwDNFHfHJTRyj0Ktqwi05bCb407WLV9FR/++hExaS/h91nITVKdoXfW\nNnPNK+sA1JKuIDz+3ePc99V9LD9meYAg0LYLBWFc9p7cWq3LoWSbwnkKHIo4cwVs6fouNw6zA6vR\nSpM31LC1wSN8Jzx+D1/u+DIgu65rqQvZ9lBGnE1PjEzo2T71TTd+HzR69F4un1d+HvBHOLPvme0q\nJVCgVUkFExQhKJ0i1Gxjr4y62bFlx+K2ubnow4uoball9fbVvP3z21x+5OVIkoTX56Xv4yohuKFq\nQ8g+OlzisC9QugH0PU5dNuLirns/qwuOe6ZDL9lYs5Fn1j+D1+dlQ/UG1u1ZF1jXQ35mWQwWmj3N\nOqVUsi0ZmmQFiaIcKBorzEwrvxW+EnHZVGRHaOTXZ4H4ORDQ+m306ISSMVe6UCJ1IwTdREIH4bCq\np0ybPZ98p+gPu/mGqQf8mA4laI0qlfHp1z3iAdbU6iUmgtFiN7rRmVDCuEhO4pY2FAl3a9RIZqNB\nN0G5bdRtgb+LEor270C7cUChZJJNkklnlJebJIiEn3YGBXtjrqS1xwx+e+dEQEy+MxzCsdoSvwpT\njFoX39Tq5eEVQq6rLXMAURJhMpi4afVNgHAbV8w5tShLLOPOMXcy+YXJbKnbwkcLPgrZplOhBLfh\nuhwcikjrJX66GJIkkWpP5Zda4Wa+ee/mwLraFrWt7B2fq33vFWnx4YJ4DZHw8IkDupMsByFava18\ntOUjrCYrS95ZAog2jopKBmBI+hAK4jpGhmuJhCn5bRgLx8QKf502IElS4DgaPA2c/a4w1l5YvpCc\n2Bxdi8pIWLl1JRXJFW1ut1+Iywz16zrIMPPfM8MuP73i9ED5ZJItiRZfi65rlNFg1JQeaMjwMz4S\nE/qDyQhaW77Qnm4dbeGi9fu/j8MU3aUNHYTDqga6MWGy593QY2t1o47R9PjU4Kxyr34y3RRBkdCN\nbnQ2cpKEd0Z2YngPDbPJQEuE7izBBIPFZOCXvSJgyHJmMT53fCceaTcOJOaVzOP48uM5veJ03XKn\n3C2loUVVJNQ011Djqee5veoEY3fj7oDaxWj/mTvXn0WPdGG+5ffDUYUimDpjhNqu8IvKL+j3eD8+\n3fZpYNnq7avp/WhvPt32aaDN4/3j7+eRicJ9/Lnpz/He/PdIiOmgaVRHUSy7sDvcXfs+hyEynWoL\ntD1NewJmmVrlgbZE5XBTJKTEqsGkqaM1yd3oFGyv307vR3vz8daPw65/YcMLnP/B+QESAWBc7jhA\nvX7H53X8eRYvlynML5mPpRNbOyvmiTd8qnZuUAxxz//g/Iive222KDG6Z809rN7e9YqkgxWbajZx\n/1f3R1yvJYAUQuEfa0X3ioXlC8UKp6wsGhZ0vg8mEkHBvIeh78KD89gOI3SP7h2E3aIqErqD3uh4\nb30lR93wHu+t3xFY5tEEZ9oyByBiaUM3utHZmNEngydOGcQxA8MbAdrMBuqaWsMaoDUGgkkP1rQX\n2d26gR+qhGv438b8rasOuRsHADaTjcuOvCwwYVVgMoZeB8OeGca0ZdNE33UZda11IZ4FGfFiIr2j\ntplmj49hRW4dgbV211oATn3r1MCyVza+AsDrm16n2dNMWWIZR2UchVNWBrgsLpLtB6CDy6QbREsx\na3dpWUcxrXAaAEv7LsVpdvLOz+8AqvIg25XN+7+qddOHmyIh1aWaq5mN3VPN3wNKZ5dnv382ZN0j\n3zyiu/4UDEgdwNrFa3lj7hs8P/155hXP6/D7KiREZxvBpthTKEssY3eTaujX7GnWZc21Rsfn9juX\n9+a/R5pTNSn+qfqnTj2mYPy892dW/tb1ptEdQbO3mXW71zHj3zO4e41os3hq71OZWTiTvxz1l8B2\no7NVBZ1CJDz/w/MATC2Q1dYWh1BctKd7we+NXnNhVrc/Qleje3TvIJy60obuoDcaVv4oBnutHFhb\nd/7t1r2Bv+ubPTS2eLvPaTcOCCRJYlixO2KHkNwkBz/trA8Yg2rR0OpBMtZhdP6AJWEVd39/Lld/\nfDUAWa6skO27cejBGOT4HEwkKG7W1c3VfLf7O0C0ugqXVR7fW5AGKbFWeYzTP3a1WWkFivy9prmG\nD7Z8wPo9v5Os0mgW7cS60WHMKJzBM1Of4eTeJ1PXWscLG17g0W8f5ZpPrgFCDeOWbVh2WHVuMBgk\njsgRmemmKB1wutF1ULqHeHyewBhyyYeX8MR3T3Db57excqsa8H563Ke8Nuc1XZeF0sTSiM/IaMhw\nZAChvgudgfkl+jr1Jm8TT657Muz60ypOI9mejNlg5p15gsi7ftX1XXJcCqYtm8YZ75zRZfvfFwx4\nYgBHv3K0btm5/c7l2mHXMrt4dmCZ9rsPblOd7To0uy91o+vRTSR0EHZLd2lDe6EY2Rk0DyJPBLn4\np5t209DixdbtkdCNgwDKNbt8w66QdXXNrTgKb8Ke/ZhuucviIsbUjhZH3TjooXglKDAafYAfySLa\njl2x4orAul2NuxiXM44RWSPY3bSbJ9Y9oXvtbetOpTw9FqfVRIvXF9L5wWIIlf7ubREk68aajZ3x\ncbrxO6GnuydmgznQteGWz1Qn8asG61vEtvha+Hnvzwf0+LoaN83rw8C8BPpmxbe9cTc6HYrZ54db\nPmT+y/P5eufXvLH5DW5cfaNuu7tG34XdbO+0YFHxd1HGsc7E/JL5zCicgc0kugc0eZoCxMC/pv8L\ngGUzlvHMNL0BYapDSPJ9fh/3fPm/k6UOR05+vejrEIJIq0YAyHBmEG9V79twhHc3ugHdREKHEcls\nsRuhULIQeiIhvIHd6s1V7KlvIdHeefV03ejGvkJrqu/VtHaoaWjl5+pKJGNLyGviLN0P2sMFwYoE\no8GHOeETnIW3smbHGt76+a3Aut1Nu4mPieeln14Ku68GTwN9s+PYVtOEx+sLkXmHczVX5LfKRO7M\nPgeoZVY3ugR3jblL9//RJUczu3g21w27jqV9lwYMWrsi8Po9UZTi5F9nHkWCo/u5fqDx/i/vc9ny\ny3TL3tj8Rthte7k714BUaREZY+x8Yl2SJP467K+8NVeMwRtrNvLs989SkVxBWWIZIEyOeyb1jLiP\nFVtXdKr6Z82ONWysPjhJX21HBoD3j34/hET4bOFn3D7q9pDXDkofBMClAy/tugPsxiGP7q4NHYSW\nSOiu54+MmsZWnvpUGNBJEny6cTcD8xJpbA2VOLpiTNQ1edhT30KSs3vC0Y3fH2ePLuKLX6r4ZOMe\n6po8xNnN+Hx+Rt3yPjW+TTjy1W0dZgf1rfVUN1f/fgfcjU5FsCLBL3kxOYU0+NpPrsXjUzs6VDdX\nU5JQwpziOby44cWw+0uwW6iqb8FssIYYzym9ukHISXc27sSPmOQq3UCOLtHLUrtxaEGpNwb4fOHn\nAQO66YXTxTK5zV59a/2BP7huHJZ47ofnQpYt27As7LbB493+YlD6IC7sfyGzi2a3vfE+QjF0vPOL\nOwF0PgmRcE6/c/jbl3/jx+of+azyMwamDeyUY1FaP69dvLZT9rcv8Pl9LN+ynKGZQ3Xf54lvnAjA\nW3PfosnbhNsWapwbycvisiMvY3zueCbmTeySY+7G4YHulHoH4egubWgXTnvss8DfH3y/kwX/+ISH\nV2xiZ61wIC9KEaZhU3qn4bSaqNzbhMfnJ7E7c9GNgwAOq4mZfYVh1K56cc3uqmumLuY9zLFrdNsq\nk//DzSztfxnBE2uPz4NkEkH991Xfh2xf4a7guLLjQpYrcNl8eHx+ttY0YTHps0GK3wLA3JK5unU/\n1cjKhJhuafihDpdFGFaGc7FXJvebajYd0GOU3m9QAAAgAElEQVTqxuEJv98f6BICIsC1Gq0hzyhF\neWU2mOlMGCQDJ/U66YCOW4oKIhpOrzidt+e9DRAwSAZ4beNrPL3+6f0+hhNeO2G/97GveOfnd1j6\n3lLd5/D4PDR6GumT3Id0Zzr5cflR9hAKt83dTSJ0o010EwkdhLZrg9nY3VIkElZt2hP4+8MfRF3x\n99trAy0flZZoRSkubGYjv1WLGje3s3NdfrvRjX2FVa5lH3vrh/j9fj7/dTsxqa9iSVInaIPSBoX9\nuxuHNoJLG9btXofNHrk3eGliaaCjghaKI7Zkrgos0yoSmjxNXL/q+sD/A1IHhN1/Z0/0u3Hg8dLM\nl0LqthVkOIU5XTcZ2Y3OQFWzOt78Y7xo33dUxlGBZW/Pe5s1J6wJeHcYDYdmUmxRj0WBv9vbMSnV\nnopBMrC7Ue388H/L/4/rPr1uv49nzc41bW/URfhyx5eAXtXU4hVqt7E5Y3+XY+rG/wa6Sxs6CK1R\nloQgEloj1P13Q49Wr4/K2iaSHBZKUsWku6q+hRizMdDBoVuR0I2DBS0e9b5+6L+b8BgrNStTWbH4\nRWKMMfR/oj8AD0588EAfYje6CMET64e+eSjsdpPzJ5NmT8NkMJFiSwksv3P0nTR4Gshyii4eHsMe\nFN5e8Uho9bay9L2lgdesPHYlLouL4ZnDWf7b8s78ON04CJBsT47YslNx11cm/t3oxv7gsW9VI+Ah\nGUMAMSZVPFYBqKU2fx/3d9buWhswLjzUsKTPEnx+H0v6LiHWEtv2CxAeCw6zgwfWPsADax/Qrfuh\n6gdKEkq64lC7FH6/P2Dy6/Or85Zmr0jchVNBdaMbnYVuRcJ+wCObsGnr/g+n9k37gz5ZceS7Hbpl\nrV7//7N33+FRldkDx793SnojgRAICRB674hSRIp0ERBFEbAhi2L/oa5rXXWtq+vu6tpRULFgAaSI\nKKD0DqGDSAuEkE76tN8fN3NnbmYS0gs5n+fx8da5LxnIzD33vOeQlJlHZIgfIzqpH2Qdm4boilb2\niJUUXlE7XN8jWlteFn+OlBxXlk172zOE+ITgY/Th8b6P83Cvh2tiiKKKlCYDYPH1i3l10Ks83Ft9\n781G1zl9o/oyNm4sTQKbAJDvcHX/cGayrTixgi3ntmjbnanvbw15i+taXUePyB5E+keyeLz3Io7i\n8qEoCj4GH6+FN4UoK2cbYvcMGEVR2HLLFtbdtE7b1sCvAYOaDar28VWWIJ8gHuv7WKmDCNp5Zs/s\nMYBJSyaVqzVk0Qy26uYeeD6bdZYn1z/JxYKLWiChuBoIQlQGyUioAJtdjfzlFbgCCXYHyIwHyMyz\n0jk6FKvdzulU9RezxWbn4LmLtGkcRJvGwex4chgNAnx4Z+0xQK2bEOwnKbyiciRkJWBUjLpCZ2Xh\nZzYSHeZPQnouu06lszf1AAExkP3nvQy9pql23NQOUytryKKWKM0Xw5ig4lulOYMKzuAAhgK3fZ7x\n+99u+s2132DmxQEvakHp8vRxF3WP2WiWQIKoFDa7+p20cUBj3fYAcwAB5oCaGFKtEuITwrnsc173\n9f28L/8Y8A+tEOqlWO1WbA7PIuLVaX/Kfm3Z2T2oRWgLrm1+LSCBBFG1JCOhHNY/pvZbdWYk5Flc\nqURWu53MPAu/Hjrv9dz6IiPXQoifiUV/cc3Ly8q3kpCeq80RjgjyxWBQtEDDsSSZHyrKxlk9/5dT\nv5Ccm8yvp37l2yPfAjDy25EMXzS8Qq8//crm2rJizAHgu1nDmDkwrkKvK2q30swZds9A8NhXmNHg\nLNro63aoyaiQnJvMK1tdvdy9fdFTFEWCCPVItiWbpJwk0vPStRtBIcojz5YHVE37xctBl0ZdAPjX\n4H+x+ZbNrJ+ynts63abtf2L9E6V+LedTf2er3pqw5tQaujXqxrDYYdo2X6OvVlCyuAwMISqDBBLK\noVmDAPq0aKD1ly9wq5Fgszu4e/527vhkO+k59W++45m0HKZ9tIXU7AJC/c26dplZ+epNX3HTF6b1\na+51uxDepOel02NBD97Z/Q4PrnmQFza/wANrHuDZTc/qejqn5aWxPmE9FruFN7a/QfwF7y2a1p5e\ny4mME7ptdw+K42+j1YJUilENeLVo0AijQW7wLmfuGQk3tbup1OcNb64GrgyKQfc6RqOdnoW/98xG\nA09teIrMgkztPJnDKgB+OvETA78ayLt7363poYg6LM+qBhJ8TfIk2ptZXWdxe6fbuSr6KgLNgYT6\nhpZ5euLeC3s5n31e+1k38Gug7XPWT6sOybnJHEw9yJDYIbouGUbFyKqTq2jk34gB0QOqbTyi/pFA\nQjkZDYqWkeBebNFqd7ClsGNBQT0swvjSikP8flSdDxzib8bkdsPlbJcZFqB/kvfYyPYE+Bj5+/hO\n1TdQUec5UxP/t+d/AOy5sEfb557qd8OSG5i9eja7k3Yzb/88blnu2abvePpx7vv1Psb9oE9nVBSF\niT3VWgmKMQeHw0Cob9nmY4q6x/3Gvugc4p9v+Jm1N671et4rg15h/RRXVw9nQMFmt2lBVbNR0aWw\nT2ozqdL7uIu6xz14dTTtaA2ORNQ1mQWZ7E7aTVJOEkO/GcrGsxsxKSbp9lKMqMAoHu79sK7IpKIo\nWtHTS/3c3tzxJlOXT2XcD+O0jIQGvq5AggNHtdVLO33xNABtwtowq+ssbftLW18iPS+dJkFNSsye\nE6KiJJBQTiaDQctIcA8k2GwOnL8/3Ku+1xfu9SJ8jAbdfOCzhS0ei84Rnj24FQf+PlLSeEWZOKc1\nOCXnugrafXnYVWQqKTcJQJdKXpR7Vf60vDRdZkJEYUtSo99ZHDZ/+XtaDwSbg7Vl55dLp6jAKCL8\nI7yeZzaYCfUN1dYVRcFkMOnm0JqNBiL8XOc/e9WzlTRqUZdNbDNRW44LlalTwjuHw8H+lP3a598f\n6X/Qf2F/pq2YxtBvhpKUk8TOpJ34mWRaQ1l9MeYLAFqHtS7xuF9O/QJArjWXEd+OAMDq0H8fce+e\nUJVyLer36iCfIKICo1hy/RJt397kvYT6hBZ3qhCVQgIJ5WQwKF4DCRa727Kt/nVwCPJzfemOT8jQ\npYA7Awm+JvlrJyqu6Ac3uJ4A772w12Pf4bTD2nKOJUe370DKAW15yo9TPDITxl11HlPQYaxZHSo0\nZlE3aEUSKbkWQmmYFJNuzrvJaChzlXFx+XMPQEnRRVGc/+z6D1N+nMK8ffMAeHv3216Pq870+stF\nh4gOjG81npTclBKP89amtUVICwB6RPYAwE7lBxIeXvswM1bMYH2CK+vN+bvCmUXh/oAl25Kt+70i\nRFWQO7pyMrkFEgqsroCBc5u6vf5lJOS7FZ78vxHtAHhyTAf6tGiA80fjrWq5EGVVNCMB1KcA7k/2\ninP64mksNov21MD9xvFs9lkADqeqgYeM/AzWpr0JQP75sRUet6j93OeaVnTagdFgxOqwapksPkYF\nB+ovw/J2FBGXH/ebF283KkIAWsvYE5knAM/6Ks1D1FpTubaytzEU6jSRpNwkdift1rblWfN4Zesr\nZBWoBcHzbfmE+4XrzhvdcjQrJq7QpsJVdkbCqhOr+Pnkz+xM2sns1bO17c7vQc7PKfdaDYBu+oYQ\nVUHu6MqpuBoJ2fmum5v6GEg4dsHVeSE6TP0FdtfAOAa3i9S2+0ggQVQC542+uzs738l9Pe675Lk3\nLL2Bnp/1pNv8bmxM2KhlMhQ9Zl/yPl7c/CIAlvSeYJd00frAfY5s0akNZWVUjFjtVoa0a0Swn4l2\nUSHaU6T5I+dX6LXF5cO9f32BXQIJwruUPDXgtOSPJXwY/yHbErcBaq2V+BnxzOk+B4C2DdrW2Bjr\nsqQcdSrkc5ue07Z9e/RbPjv4GR/EfwCogYTRLUfrzvM1+tIsuJn2XaKyAwmPrHvE63aLQ/0scX5O\nNfRvqAtyXMi9UKnjEKIouaMrJzUjQf1FkeNWF+BinlsgwWbHYrNjt9efKQ7OFo4vT+yi255ncf2M\nGgVLJWFRdtsSt3H3qrs5lHoIgFe26Wse/HbTbzzQ8wGvEXgfQ/FV8Z/d9CwFtgK6Nurqse/mZTez\n4sQKAPISr6/I8EUdZTC4PiYf6vVQmc83GdSpDbf1b0n8syPoHhNGnjWPJoFNaBLUpDKHKuqwQHOg\ntiwZCaI4CVkJ2vJbO98iKSeJMXFjtForzifTzg4yomxeu/o1AGwOG9sTtzN33VyyLdmAGkDIseSQ\nbcnGz+THHZ3v0M5z1qQwFN5W9f28b7WM12IrnNrgNgXPvYZPpH+kxzlCVCYJJJSTe0ZCRq7rQz/X\nLaiQll1Am7+t4PHvPOdrX46c2RhjujRhSt9Y3b58t+yM9k2CEaIsTl88zR0/3cGmc5uYvHQyPx7/\nUbe/aWBTGvg1QFEU/E3+KCj8te9f2TltJ6AWMts1bRebb9ns8drnss95TVX04JAWffWRez2NK5pc\nUebzQ3xCtIKfTsv/XK51HREC4C/d/qItSyBBeHM847jX7WG+rqlYQ2KH8ObgN3U3uaL0YoJjmNx2\nMn9m/MntP93OyhMr+XT/p4CaZXAm6wyg/szdsx99jeoDsgBzgLatop0bsgqymLdvHl8f/hpQMy7v\n7X4v4KqNUHRqA4CvQR1Lh/AOPNLbeyaDEJVFAgnl5F4jIS3HVRhp56k0bfmu+dsB+Hr7meodXA3p\n9MxPAFzZyrOiufMX6hOj2+NrMnrsF6IkRQMHH8W7uizM7DKTz8d8rq0bFAN7Z+zllg63YDaY2X7r\ndp644glMBpPuqd/CMQuJDVYDXim5KfgZXdMWBjcbrLuen1HmGdY3N7W7iWZBzWga1FTb5t6ir7Sa\nhzTnfPZ5bV0K6QlvGvo31JarM5BwOPWwbj64qH1OZp7kaNpRtidu97rf/YbWoBgY1nyY1+l6onTc\nAzOg1k0ANZDgDCy3Cmulv3kvDCSMjXPVUbpt5W1ep2CWxqf7P+XKhVfyxo43eH7z84Ca9eB84HE2\nS63lVLTYIrjqZlzb4lpdYEOIqiC/acrJaDBgLezKkO4WSHh91ZGaGlKt0TjEcx65c3aHVBIW5bH8\n+HLd+rH0Y9ryvd3v1X0JL8rX6Ktr2ej8wI8MiOSe7vcA6rxTH6MPyyYsY82Na2gW3Ew7PtwvnHU3\nbgRgzjUlt4USl48n+z3JikkriA6K1raV58t5iE+I9kUUILsgu1LGJy4v7jcl1Vkj4YalNzBtxbRq\nu54om19O/cLY78cycclE7Ybyb1f8jetbu6bauQfIRcUlZid63W61W8mxqoGEoj9z94wEZ9bAzqSd\n3LD0hmIzSUry+vbXPbZFBUYxIHoA4GpBmWfN010fXEGFIHNQma8rRFlJIKGc3DMSMnLlCZO7SC81\nEJwZXorEEUQ5OCtUF7Vr2i6MhrI9JR4aOxRQb/Dc2/D5Gn2JDYmloX9DXeGz1mGtCfAxcfDvI3nk\nWilgVZ8ZyvGRGeobSkJWAn9m/AnARctFAK0omhBFOec9V7VJSyZpy1vPba2Wa4pL+3T/p3T5tAsH\nUg7w4JoHPfYPiR3C7G6zvZwpKsPAZgO9bjcbzGTkZwAQbFan6DozBNwDgUULLW4+6zmlsjyGxA6h\naVBTwv3COXNRzXS+aLmIgqLrPOX8TiQBJlEdJJBQTgaDgq3w7jjfarvE0Zc/q1vniqZhnmng069s\nTnSYP2O7NvXYJ0Rpxc+I56l+T2nr5WnN93z/51k+YTl+Jj/d02b3iH6nhp205XbhahtTfx+jLrNB\n1D/uhRdLyxmsuu6H6wC0wl2twyS7RejtvHUnfaL6VEtGwu6k3RxJc2VQLvtzWZVfU5SO82n0H+l/\neN0fGRBJ06Cm/HfIf1k+cbnXY0T5uReqvLXDrcwbMQ8Af7O/1tUhMlAtYvj+8Pe5uf3NuhpLqXmp\nutcr6/QCZ5ZB2wZtWTx+MQD9m/bXPkvcs9wy8zMJMgfpsuWc34sCTDKtQVQ9CSSUk3tGQn49bPNY\nVJZb20tvXRlaNAxkw+NDiAqV9nmibJxzAR/o+QAAHSM6Vuj1fIw+xITEABAbEqvb7jSpzSTeHvo2\nABNbT6zQ9cTlozwZCUW/RE5eOhmAIB9JOxV6ZqMZk2Kq9NZx7hwOB9mWbI/pDM4bJFF7PLH+CQAW\nX7+YES1GAOi6C10dczUxwTE1MrbLmfsDivt63EfvqN409G/I5rObOZ9zHn+Tv5aR0C68HU9c8YTu\nIUN6fjoAj/V5DFCDx98d/Y7k3ORSXd+ZbXBTu5uIC4tj7/S9vDv8XW1/iE8IGfkZWO1WMgsyCfEN\n0Z3vbAVpR+5NRNWrWIPsesxoULSn8PmWS/9jtdsdGAyX79NMZ9vL127wbKEnRFnZ7DYtPW/N6TUA\nXNv8WgDah7evtOuYDCZMBhNWu1VXbNGgGBjUbBDxM+Ir7Vqi7ooMiCz3jZZzTi3AFwe/0JZl/qrw\nxqAYKlztvSRfHv6Sf2z5h26bgkK+Lb/KrlmfZORn4G/y1wWmy+LD+A916/4mf+JC43j96tfp37Q/\nQ2KHVMYwRSk52zqObjma+QfmE+YbRmRAZInZie0atOOnEz/RpZHaBv3lrS8DauHdpdcvvWRm44Ql\nEwC0AEHR44N9gtlwdgM9FvQA1O4MRfdD+QLfQpSV/C0rJ31GwqWnNmQVWC95TF3mrBMR4m++xJFC\neLctcRsPrXmIpzY8RZ/P+5CSmwKoT8p8DD5a9oDJYGLx9YtZNG5RpVw33FdNSZTqxqI4faPUnuAO\nyn6DF+Hn6mLz0taXtGWZvyq8URSlXBkJVrtVC0CsPb2W+fvnez3O2UrOacn1S7iiyRXVVpfhcuVw\nOEjMTmTAlwOYvmJ6uV/HmYHn5N4pZkKbCYT6hpb7tUXZOacMtAprBagdNBr5NyrxnDs638EP43+g\na0P9g7WTmSf55sg3JZ7r3rHFvYaTuw1nN+jW+0T10a3P7TOXOzvfydUxV5d4LSEqgwQSysloVLC6\nTW0I9HH9sm8Y5Jna73xif7nKzFO/hAT7SZKLKDu7w84dP93B6lOr+eHYD1jsFpYdV+fsfrzvY485\nw3GhcVrtgoqaP3o+93a/l4ltZAqD8O7Zq57l7aFv0zK0ZZnPvaHtDQSZg2gR0oKekT217RJIEN4Y\nFEOZU5Ktdis9FvTg2U3P8vq217nv1/t4bftrxR7r9Hz/52kZ2lLLyhLl9+aONxm+SJ1bvz9lf7lf\nx+aw0TigMXN7zwWgd+PelTI+UTHOegNns89esg2w0WCkVVgrr5kHm8+VXHjRvcOPe90md0W7VF3V\n9CrdeqhvKA/2erBcNaSEKCv5W1ZORWskdGoaytYTaoGVf9/cnVs+2KI7PjPXQrSXIoSXC2egJMRP\nMhKEJ4vdQr413+u8cJvdpqXyuXtt+2tM71T+JzulFR0UzV+6/aXKryPqLl+jL4OaDSrXuQbFwOS2\nk5m3fx4nMk8QExzDlHZTaBRQ8lMtUT8ZKP3UhhuX3ojFbtGmZX139Dvd/tS8VF0ROHAV+wRoEdIC\nUKvRO/vRi/I5lHqoQue/svUVogKjsNqtmAwmrmt1HYdSD/FY38cqaYSiLIoG1yL8XZllWxK3eDul\nRN9d9x0Tl0ykc8POJR7nPv2tuIK8X475krm/zeWW9rdw+uJp+jXpV+bxCFFZJJBQTkaDAavdgcPh\nIN9io3GwL89f35mnfthHTIMAvph5hS6YcNlnJBRObQiVqQ2iCIfDwZ0/3cmupF1sm7pNm3PolJaf\nprXGK+p4xnEUlEt++ApRmzULbqYtxwbHVkuATNRNZZnacDD1YIn7vzv6HXd1uUu3Ldeay+iWo7m9\n8+1avRkJJJTPHT/dwbbEbTx95dO6lsEA+bb8Yp8oF5WSm8JnBz8DYFTLUZgMJsL8wvjHwH9c4kxR\nVVZOXElafpq27l6HQKH09c4+HvEx3xz5hpahLVFQyLHklHj8B/EfALBo3KJip7E0DmzM/FHepy4J\nUd0kkFBOpsLCiXYHFFjt+JqNTOvXnJv7xGAyGkjMzNMdfzHv8v6QdgZKgnzlr5Rw2Xh2I7N+nqWt\nrzm9hlEtRwGwPXE7c3+by60dbgXg1UGvckWTK8i2ZDPu+3HYHDbG/zAegG6NulX/4IWoJI0DGmvL\n5S3CJuoHBaXSqq0fSz+mW3c4HORac4kOitYVrTUZTBJIKKNcay7bErcB8PdNf/fYvy95H70a97rk\n6+y5sIfnNz2vrdvstkumzouq1ziwMY0DXb+33bMpXx30aqlfp09UH62GQYA5QFd8tyj3TKSiD1yE\nqK2kRkI5GQsDCTa7g3yrHV+T+qM0GdX/m436H+3l3iKyoLCDha9Z/koJl88OfKZbP5FxQlv+aN9H\nJOcm86+d/wLUonThfuHEBMewc9pOpnVU25MZFSOT206utjELUdn6NXWlnrp3BxGiqMro2jAsdhjd\nGnXTtZvLteZy1cKrtDn47nyNvlrvelE6zmLA7npG9tTmpW89t7VUr/OfXf/hcNphQJ1q4pzaIGof\nZ6vN0maaFBVgCigxI8E9A6JoHQQhaiu56ysnfSDBpgUSnBoG6Z86FVzmgQRnK0yTQf5KCZfzOed1\n6xkFGQDc9dNdrE9Yr9sX5hemLRsUA4/2eZT4GfHsnr6buLC4qh+sEFXE1+hLp4hO6rKpfF9CRf2g\nKEqFAwkB5gAi/CK0m91DqYfo+3lfsixZAMSExOiOb+jfkNS8VCm4eAkWm4XE7ETAexZCfHI8q29Y\nDaiZBqXhXsPCYrew/fx20vPSK2G0orLN6qpmVzo7SJXVpTISjqYdBeDf1/xbivGKOuOSd32Konys\nKEqSoij73LaFK4rys6IoRwv/36Bqh1n7OKc2WO128i12fE36VLSIQP2Xxcs+kFBYeNL5cxH127rT\n69iVtIsjaUcAaODbgMYBjckqyCIlN0UrVtQxoiNhvmE0C2pGy5CyV8QXoq5wTmko79MsUT+UtmuD\nt2CDv0kt6Nw4oDER/q5AwoIDC3THFW1f1ymiEzaHjU1nN5V32PXCv3f9m+GLhnPm4hk2ndP/rIY3\nH87yicuJ8I9gULNBpOallvn1E7ISyCzIJCk3qbKGLCrRda2uY/2U9VoryLLyN/mz9dxWr1kJedY8\n7v/1fkBfU0eI2q40j48/AUYW2fY48IvD4WgD/FK4Xq8UndrgUyQjoWiGQr7tMg8k2BwYFDBIIKHe\nS8lNYc6vc7Re2q3DWrNw7EKCfYI5dfEUg78erB07p/scfp/yOysmrcBslEKd4vLlLJwlUxtESUrT\ntWHrua0kZCXotvWM7KkV/IsKjCI6KJq0/DSSc5O1KWX/1/v/eHvo2x7V4Ac1G0SITwirT62uvD/I\nZeKrQ19x49IbKbAV8Mn+TwD45dQvHsf98+p/EhUYBaj/xvNt+aV6fYvNQuuw1lzX6jptW/+m/Ss+\ncFHpFEUptgBiaRTYCkjJS+HpjU977Pvb+r9p2QrFdWsQoja65EQsh8Pxm6IoLYpsHg8MLlz+FFgL\n1KseNc4n7wU2OwU2u0fgoOgN9ZbjKUzr17zaxlfdrHaHVh9C1G+JOYm69Tu73El0UDSB5kB2Je3S\n7YsOiq7OoQlRY9qEtWHt6bUSMBMlUhSFAlsBY78fy5i4MczuNlu3/2DKQe5cdaduW/OQ5rw3/D36\nfK4WdYsKjNJuaq/5+hoApneczoxOM7xe02w00zSoKam5ZX+Kfjk7n32eF7a8AECvz1yFE1/f/jo+\nBh8+HfUpAaYAUNT3zcmoGLE5bKW6hsVuwWww8+KAF5nQegLZlmyujrm6cv8golY4l30OgJ9O/MTr\nV7+u27fq5CpADUK5/10SorYrb0WXxg6H41zhciLQuLgDFUW5G7gbIDa2fPOKaiNjYS2A3AL1w6Kk\nIoNBviZSsgqqZVzVzeFwcP3bG9hzJqOmhyJqiR+O/qAtfzLyE3pG9gS8zxmVysSivnA+ySraJk4I\ndwbFQFJOElaHlXd2v+MRSHhv73se58SFxul+lzYOaKyrMg/QLrxdidcNMJU8f9spOTeZUJ/QehEQ\nc2bVeXN/z/uLbUtsMBiw2UsXSCiwFWg/y95Rvcs+SFFnDIgewM8nf/bY7qy7ATC+9fjqHJIQFVbh\nR8gONQev2Dw8h8PxvsPh6O1wOHo3atSouMPqHGdGQo4zkGAqvl1P35bhZOXrixitPZzE19tOV90A\nq0lWvlWCCAKAk5knuenHm/jy8JcALBi1gF6Ne3lE17s26qq1HgswBVT7OIWoCSE+IQBcLLhYwyMR\ntZlBMWB1FF/00FtBxKf6PQWotWhAzUhoEthEd0zR9aIuWi6yNXErF3Iu6LY7HA7+u+u/nL54moz8\nDK75+hre2fNOqf4sdd3Z7LPF7iupJXFpMhIcDgdvbH+DTec26QouisvXC/1fUOtBherrQb24+UVt\nuWhHFSFqu/IGEs4ritIEoPD/9a4yTLCfmszx0fo/Ac+aCADvT+vFqocG4Wc2kGtxfahsPp7CbfO2\n8ei3e6tnsFXoyPmsmh6CqCW+OPgFB1IOaOtdG3XV7f/9pt8J9Q1lVtdZfDD8A/4x4B+6Tg1CXM4k\nkCBKQ6H4tGaL3cK6M+t022Z3m02jAPUhzfxR85nbey6hvqEYFIP2WnGhcVrXkOJMbT8VgMV/LNZt\nP59znvf2vsfo70Yz4MsBAKw6sapsf6jLxPDmw7XlCL+IYo8rTSDhYOpB5u2fB1w6yCMuDwHmADpG\ndPTYnmtzZalJhypR15Q3kLAEcE62mwEsLuHYy9KQDpHEhPuzaMcZwHsg4dpOUbRtHIyf2cixpCy+\n3q5mIEx5f3O1jrUq/XLw/KUPEvWCs5Lx5LaT2XLLFgyK/t9EmF8Y66esZ1CzQYT5hTGu1biaGKYQ\nNcL5BbF7ZPcaHomozYpmcLkXXtx1flfRw5ncdrK23CK0BdM7udLxt07dyo5bd7D4+sUEmEvO/prU\ndhIAb+18i1uX31riFBxn/YW6zGKz8Knp05wAACAASURBVOq2V0nKKf452PhWapr58onLeWXgK7wx\n+A1tX4R/8YEEg2LA7ii5wLazoxHAhNYTSjtsUcf5mfzIt+oLcfZprNY2mdRmEkNjh9bEsIQot9K0\nf1wIbALaKYpyRlGUO4GXgeGKohwFhhWu1yu+JiND27tSkHzNxU9t8C/c9+iivby95liVj6262O0O\n3ln7h7b+0sQuNTgaUVvM7jb7kl9ahahvWoa25KdJP3Fbp9tqeiiiFis6dcFit2jLziDDI70eAeDF\nAS9q2Qje+Jn8tLajZbHnwh5e2vKSen2bxWO/yVDe8lq1x//2/I8FBxbw1Ianij3Gz+RHA98GxATH\nMDputG5fSZ9xJoOpxBoJDoeD9/a8R0P/hqyfsp4OER3K/gcQdZK/yZ8sS5YuQJhrzcVkMPHsVc/W\n3MCEKKfSdG24uZhd9T5s5pzeAN4zEpyahLqKIL3202HdPovNjrmauh2sO3KBPIuNEZ0q52lCao6+\ngGSLiMBKed2qtOP8DlqHta5QCx/hnTOV02goPqgmRH3WNKhpTQ9B1HLOwmstQlpwIvME+bZ8LRjg\nzBLoHdWb+BnxVTqOzec2cyj1EOn56dq2/tH9ifCL4OeTP5NnzavTxXJT8lIAtNaY3tgcNo/MupcH\nvsy+5H0lvrZBMZQ4tSElL4UzWWd4rM9j8l2knokLjSOzIJMP4z/ktzO/ER0cTbA5mEBz7f/+LIQ3\n0q+vAoJ8XYEEnxICCTHhxUeuc/JLV9m3ovKtNmZ8vJVZC3Z43X8uI5cCa8mpeEVZbfoam3GNavcv\nwqyCLG5beRv/t+7/anoolyVnKqdRkUCCEEKUR0JWAgBXNr0SgIlLJrI9cTtP/P4EORa1q4K/yb9K\nrv1C/xeIDoomKjCKc9nnmLx0MjNXzQTgzcFv8u6wdxnVchS51lx2X9hdJWOoDouOLOK7o98BcCH3\nQrHH2R12j8+zMXFjeKxvyd3OjYqxxKkN9/96P4BHkEJc/pw1Ev6969/svrCbZceXEZ8cL4WnRZ0l\nv8UqSUkZCUM7FF+FNaug+OrMlemdNX8Uuy8738qVL/3KUz+UHGUvKt+qBkHaRKptpiKDfcs/wCqW\nnJvMR/s+AvRzE0X5ZBZksuz4MjILMrVtzpRcCSQIIUT5OHvNX9fqOkDNULj9p9tZenwpc3+bC1Rd\nt5vxrcezctJKrx0JnFkRzYKaAfDsxmerZAzV4blNz2nLFrul2GkINrsNg6HsX5ONipEsSxZL/1hK\njiVHCwABpOSmEJ+sZpOMbjm6uJcQlylvbVgPph4kzFcKT4u6qe5PdKtBmXmecwe9CfI1cWVcBJuO\np3jsy86vnkDCW78cBSA6zPNJRkau+uf4esdpXrmhq8f+4uQXZjA8OKwtY7rW7qrDj//+OFvObQGk\nvU55HUs7RlxYHAbFwFeHvuLfu/4NQGxwLEObD9W+jMnUBiGEKJ8Gvg1Iy08rsctCVWUkOHl7Uu7s\nUtDQvyHgypyoy8wGMxa7hXxbPgEGz+CMt4yE0nD+bJ5Y/wSgdmxZe9NazAYzqXmp2nHStaj+8fZv\n1+6w06ZBmxoYjRAVJxkJFRDrPmXBUfxxAIG+rg+jYF8TDw5Tf2lkVVMgwcnu8Bzo+78dB8CgFN92\nypt8ixpIKGlaR23h/uHt/CIkSu9s1lkmLJnAS1tewu6wa09UAE5dPMW8ffOYf2A+ACZF4pNCCFEe\nn4/5nHeHvYuiKExqM8nrMVVdzLZrQ/WBwssDXybIHESXhl20goBBPkFatsTO8zs5kXGC89l1p3uT\ne3aA8ynwFV9cwc7zOz2O9VYjoTSyLdm69cyCTD7c+yHgau/5WJ+Sp0eI+qVdA89MBSHqgtp/B1iL\n3dg7hhYR6gf6pW6mA93qKUzpG0P/1urNbHVlJDhZbJ7z9j7ZeAKghO7VrnP3n83Q1i9k5QHQIMBc\nWcOrEsuPL+dompqREWgOpMBecIkzRFHOQMyXh7/kpS0vseb0mmKPlYwEIYQon5jgGPpH9wfw2nMe\n1CfpVWlqh6ksHLOQMXFj2HDzBr4Y84XuhvrhXg8DsD9lP+N+GMewRcOqdDyV6WTmSQAGNRvEsOau\ncf988mePYx0OR7kCCa9d/Zq23CdKbe33zp53SM1L1bpwNAmq3VmcouqsvXEtAG0btNW2tW7QuoZG\nI0TFSCChAhRFYfGcATx3XSd6NW9Q4rHugYQQP7PW8SEz13sgodPTK3nz58qfy19SQUWr3cFzS/fz\nwy41LW9fQgYb/0jW9n/w+3HG/Hs9K/epcziPnM8CoE3j4EofZ2V67HdX5L9zw86czjxdg6Opew6n\nHubmZa7mLV8e/hKAOd3nML3jdH6+4WdeHPCitl8KSAkhRMUV1xVBKWP2YFkpikLnhp0B77/Pw3zD\nMCgGVvy5Qts29JuhHq0ra6PkXPU7zcwuM5nQeoK2vXlIc91xFrul3BkJob6hrJ+ynvVT1vPxiI8Z\n1XIUoNaVeH/v+0DVB4NE7RXhH0H8jHi+ve5bbVu4X3gNjkiI8pNv/BUU6m9mxlUtLvnBHujjekob\nGxFAeKBauCg1O9/r8dkFNq2uQUXlWVyFhAq8ZCS4j23ehhM8+JVajXnsf9ZzywdbOJGspuklX1Sf\n5K8/pn4QHz2fReMQX0L968YH4pCYIVhsFs5mn+XpDU+z4MCCmh5SnfD14a89tt3R+Q5mdZvF3D5z\niQqM4rpW1xEbHFsDoxNCiMtTx/COtA9vX9PD8GA0GD2muCXlJPHj8R9rcFSl83vC74A6xbFDRAfW\n3bQOQNdlYf7++fRc0JNVJ1eVu3hwqG+o1trxtk63AbDm9BpWn1oNgMkgUwCFS1XXPRGiqkggoZqE\nBfhoy7HhAYQXridneabZO7zUMagI96KQFpvna/v7eH5Qzpy/XVse/PpaWjy+jNzCgERajoWUrHzO\nZ+YREVh7OzWA/svBq1e/SmyIerP7/bHveXXbq4z8dqSufoKTzW5j2fFldeIJS1XbmbSTAdEDWHL9\nEm3b7Z1u9zjum3Hf8OOE2v9FUggh6oLWDVrzzbhv2H7rdqZ3nE7zkOa1MrDg9NSGp7hYcLGmh1Gi\nhYcWAtAooBEAPobC72K5ruxL94DIsfRjFb5m+/D2/KXbX3TbpJaQcCfdrkRdJYGEahIV4kpRjA0P\nwGQ0EBZg5kRKtsex9sqNI3Axz3UzbLM7sBW5gLdgxs8HPIsnLdx6CoCUrHx6vbCa9ceSuZhfus4V\n7hwOByv/XInFVvZz3R3POM4n+z4p8ZitiVu1ZV+jL7d2uFW3PyErga3nthY9je+Pfc/jvz/u9Wl8\nfWCz2/j84OdkFmSSnp9O44DGtAxtSfyMePZM3+O12nSAOcAjPVQIIUTF+Bp9mdtnLkuuX8JXY7+q\n6eEAancJb2pzVkJidiIAcaFx+BrVhyDOtpYfxH/A+oT1AORac7VzpnecXuHrGhQD93a/l5WTVmrb\nqnp6iqgb3h/+Pu3D20s3MVFnSSChmjQJdQUSIoLUD7D0HAuLd5/1aCPprSBiRaTnqIGCvi3CPV7/\ncGLZnx5sPu56gn86NbeEI7378fiPzP1trvZkoLymLZ/GP3f8s8QnIBvPbgTQWml56+H71IandFkJ\npzJPaX2mE3MSKzTGuurX07/y8taX6b+wP8m5yYT4hGj7pAaCEEJUP4NiqDW/f4s+YXf6x5Z/1NpM\nvofWPATA430f17a51yrYeX4n96y+hxOZJ/A3+bNg1ALm9plbadePDopmz/Q9vDP0HXo37l1pryvq\nriubXsk3477BbKwbU4SFKKp2fCLVckfSjrAxYSOHUw+X+zWahBU//ykzVx9IsLplDLhPc3hn7TGv\nmQKXcrSwKGJco0DA1bYRICE9R3fszX2rfp7727vfBqhw94TMgkwALuRe8Lr/aNpRvjj4BR0jOjJv\n5Dxt+2uDXtMdl2fL4+qvrtZ6P686uUrbty95X6VPNantdpzfwcNrH9Ztkw85IYQQTrd0uEW3fkWT\nK7TltLy06h5OqYT6qTUL+jXpp21TFIUvx6oFhBOyErQaCtc2v5bukd0rfQwGxcDAZgMlI0EIcVmQ\nQMIlHE49zKQlk5i1ehY3LL2h3K/jnpHg9OhI9el4dr5Nt93qljGwZM9ZTqfm4HA4eHXlYV3tgtJy\nZiD8flSdA7hw2yltn8mg/yvwwvWddetBvpU7j8/hcGg37M40w/Jwf+KRcFF9vYsFF5mxYgZbzm3h\nbNZZJi6ZSL4tnxf7v6grZDOy5UiWXL9EV7EZ4IFfHwBge6L6Mx7RYgTbErdpXywuJ5kFmcU+NTqS\npnYLubf7vUxsM5HujbpzbfNrq3N4QggharkfJ/zIsgnLeHfYuzzT7xmtXWWeNa+GR+YpIz+DDQkb\n6NKwi8dNfIfwDhgUA6tPqoUQJ7aZyN/6/a0mhimEEHWKBBIuoSLBA3d+ZrWQinuHgw5N1HTxrHz9\nDZ17QcQHvtzNyH/9RnqOK2shJct7p4fiOGsiXBGnTm1wbwFpNrr+Cvzl6lYYDQqvTuqqbXt6bEca\nBJjpFuM5Jx4gwEuhxpK4zz386vBX5X7av+XcFm35nl/uYX3Cep7f9Dw7k3Zy16q7GPf9OEDth+2t\nP2/L0Jb8vf/fmdphKgCT2kzicNphJiyewIazGwjxCeH5/s8DcDDlYLnGWFs5HA76L+xPjwU96PJp\nF55c/6Ruf45FzVKZ0WkGz131HAtGL/A6JUQIIUT91TykObEhsfSP7k9MSAy3tFezFF7d9io3Lr2R\nc1nnaniELp8f/ByAc9meYzIoBvxN/lqW5HNXPSdV9IUQohQkkFACm93msW3NqTXlfr0lc/qz8sGB\n2rrzaX9OgT6QYLXrayRkF9g4neaagpBnLVsNBWdc4uHhbQHwM3u+7c+O68jjo9Rq0JN7N2PJnP7c\nP7QNk3s3Y9fT1xIeoAZAPpjem/ZRwQB0bRbKx7f1KfHapzNPY7FZ2HthLw6HgyxLlm7/Gzve0Jb/\nteNf/HP7P0t8vd1Juzl98TTbErfpqh7PXj2bX079oq07vxDc0/2eEl/vsT6PsXPaTq5vfT3gqtA8\nvPlw7YvEf3f/l/0p+72evz1xO1d/dTVrT68t8TrVLc+ax/GM4173peXr004X/7FYt55rzUVBwc/o\nvYe5EEIIUVSPyB4ArD2zloOpB1l/dr3HMQW2AiYsnqA9/a8unx34DIAnr3jS6/5si2fhayGEECWT\nQEIJ8m2eT/7vX3O/1wBDaXRtFkaTUFeU2/k0P7tIRoJ7lwWns+muJ/kFZQwk2AszEkIKsyH+sfwQ\nO06qN5POaQ9dmoVqxyuKQtdmYTw8vK2WAujMXLDZ7bSODAJg5sA4+sVFFHvdpJwkRn8/mhuW3sDU\n5VN5Y8cb7Evepzvmk/2fAOpT8o/2faStF2faimmM/m40H+37iLbhbbmvx33avqI1Fz4e8bGuSKA3\niqJgNpjp0rCLbruzTeSQmCEATPlxCr+c/MXj/J9O/ERqXir3/XofO8/vLPFalSHHksOh1EOAGqQ5\nnn6cAptnrYnPD37O+B/Gew0meDu+wFagZYdcLLhIkDlI5nAKIYQotdiQWF0A+vMDn+u6Mx3POM5L\nW1/iWPoxraBxdfE3+9PQvyFDmw/1uv+hXmohxjcHv1mdwxJCiDpNAgklcKbhP3HFE7q2dt0XdOdo\n2tEKv36wr3pjn5mrDxy4T2NwynKro1DWQIKt8AbRZHDdGE7630bda7lPcfDGbFL3F9gcPDayPcM6\nRGpTJYpz+uJpAO1m9pP9n/DAGrUOwUsDX9KOy7XmanUTSmJ36P/cbRu05e6ud2sdGQAWjllI/Ix4\n4mfE0yeq5GwJd0aDkbU3rtXWowKiAPjnYFeGxOZzm7XlrIIsbv7xZr48/KW27ctDX7L3wt4qnR86\ne/VsJi+dzMNrH2b096MZv3g8vT7rxYaEDbrjjqarfz/H/zCe5NxkHA4HZ7POAmCxq3+/XhzwIjO7\nzASg12e96Dq/K10+7cKh1EOE+5f83gohhBBF5dlcn39/ZPzBe3vf09bf3PEmi44sAtTphdVld9Ju\nknKSSpyid0fnO4ifEc+w5sOqbVxCCFHXSSChBM6MBD+jH29d85ZuX2WksjcN8yPI18SeM+m67e7Z\nB055Flcg4cb3NpXpOs4aCYYiT5gvXMwnu3BaxaVqHfgUBhosVjsx4QF8OKMPkcElp76XlCo4Nm6s\nttz3877aU/aiHvvtMRYcWADAd0e/0+1z9rF2BiWe7/88nRvqi0WWRYR/BL9M/oXZ3WYzOGYwACaD\na/pESl6KtvzunnfZl6JmV4xsMRKAFSdWMHX5VN7d8265x1ASh8PBziQ16+Hnkz/r9v1l9V/Yc2GP\ntt7Qr6G2fM3X19B1fldGfDuCY2nHtECCSTER6htKUTuTdtIhvENV/BGEEEJcxmKD9Z2f3tv7Hkv/\nWAqgBbMBfI2+1Tam+OR4AFqFtqq2awohRH0ggYQSOCPrvkZfWoW14rE+j2n7is4zLw+T0UDP5g3Y\neUofSDie7HkD/scFV22BjFzPjIWSOKc2GA36QEJqdgGp2Wqae3hgyR/qZqN6rsVW+mwIZ9G+ohaO\nWQjogwnv730fAH+TPw6Hg40JG7HarSz/czmvbnsVUJ/4u2vor94stwxtyYabN2h1DioiMiCSe7rf\nQ4A5QNu2fOJyOkZ05EKO2mYyMTuRTw98CsD9Pe7n+f7PM7z5cO34okERm93GmYtnKjw290AGwFP9\nnmL3tN08e+WzALy69VX2XthLrjVXG19Rd/98t9aVwmw0c1XTq7we597KSwghhCiN78d/zzfjvuHv\nV/1d2zZv/zysdisnMk7Qu3FvIgMidYWXq5qC+v3l7q53V9s1hRCiPpBAQglahrRkx607GN5CvUm8\noa2rg8Px9OO66PrupN2sO72uzNdoGOjD+cw8EtyyEE4kZ2s37k7zNpwo82vvOZ3Opj9SsDoDCUUy\nEjLzLKRmF+DX9GvGLL66xNoPDw5ry9VtGzGma5NSX9+ZkTCl3RTeHvo2oD69d2YNvDTwJb4a+xUA\nB1MPFo7RyLoz65i1ehYTFrvaM57PPs/htMP0a9IPg6L+te0V1Uvbf6laCBURExxDi5AWXMhVAwlr\nTqsFN+/sfCczu87Ez+THK4Ne4csxX9K1UVc2nN3AsuPLSM1LJceSQ/cF3Rn13SiyCrJKukyxzmWd\n49pF13LbytsAeG/4e3x07UdMbjsZo8GoBVD2Ju9l6vKpbEvcpp3r/Lnf3vl2AC7kXuD5zWo3CrPB\nTJsGbXi418Pa8c72XYHmwHKNVQghRP3lY/ShfXh7JrSZwMQ2EwFIz0tnfcJ6CuwFXN/6etqHt/da\nq6eqOFsdu2cYCiGEqDj5rVoCRVHwMfpo6+6peBvObmDEtyOInxFPel4601ZMAyB+RnyZruFrNpCa\nXUD/l3/lxMtjAHXKQWx4AH9c8MxMaNs4CJOhdPGf8W+r8+bvG9IaRQGDQWFgm4b8fjQZgMxcNZBg\nDt1JlgVe3vpysb2Tm4b58+kdfcv0Z3MGEu7reR8hPiFefzYdIzrSyL+RdpNutVu1+hMnMk9ox438\nVp0+kJGfwXvD3+OrQ1/RvkH7Mo2nIhr5NyIhK4E5v8xh3Zl1KCjc3/N+bb/ZYKZTw06MixvH3gt7\nefz3xz1eY33Ceka2HFmm62YWZPLRvo90LauahzQnOihaWzca9NNSntn4DAB9o/oyMHog66esJ9Q3\nlHn75umOMxvUGh23d76dAdEDOJt1lt5Rvfni4Be6DAshhBCirJ698ln2XtjLsfRj3PerWhi5a6Ou\nrD29VptidzbrLHN+nUP/pv15pPcjVTIOq0MCCUIIURUkI6EMFEVhyfVLaBbUTNuWY8lh4Feulo5F\nCwIWNXHJROaum6ut+5pcN4GZeeoHa67FprWGdNc+Kpg2jYPJs5ata4TN7tCyET65vS8/PzQIgDNp\nuaTluJ4KFO2oUFHOIosBpoASj3MGEUCdTrLq5CqPY5xfBF4a+BL9mvTjzWve9LiBrkoR/mp3inVn\n1KwTBw4tM8Kd8wmMN3N/m1vsPm8SsxPpv7A/Xx1WszbeHfYu93S7h6aBTT2O/WTkJ7zQ/wWaBjYl\nOVcNFL07/F0URdHqIPxr8L9YMGoB3Rt1p0N4B9o0aKOd36ZBG66OuZpAcyAzu86UL1xCCCEqRFEU\npnecrtvWIqQFZqNZy0j46vBXHE07yif7PyE9L93by1SYe10gIYQQlUcCCWXUMrSlbp7d+gR9n+TU\nvNRizz2WdoyjaUdZeWKlts3X5HoLnG0g8yw2GgV71iw4lHiRA2czOX4h22tBxuIcOZ+F1e7gRMYJ\njqUf0YokPrNkP8dST2nHhfhW7vSAvcl7aR3Wusw3pYdSD/FUv6doEthEK6gIEOobSquwmimW1Cy4\n2aUPQk3rjJ8Rz+S2k7Vtz131HJ0jLl0E0mK36KaX7ErapS23CGlB/+j+zO4+22tbxl6NezG+9Xhd\naytnxoHT0OZD6R7ZnQWjF/D1uK+JDIgs1Z9JCCGEKA/ndDknRVHwMfho7ZqPp7taFP+R8UeVjMFq\nt6KgVOvDByGEqA8kkFAOE9pM0FoFPrJOn4qXkpvi5QzV5KWum0tHYUtG90BCnsXO2fRcDiVeLLYd\n45+FhRjf/+04Mz7eqgUfSrL64HkMPkmM+2EcNyy9gdAA1w3m8SzXdIONZzfy4JoHL/l6pXE84zhH\n044yquWoUp/zxuA3tOXBMYNZdcMqfr3xV21bSTUcqtqw2GEsGLWAtTeu5aZ2NzG3d8nZBU9c8QS/\n3/Q7C8csZGKbiQxspmatFJex8vnBz+m5oCc3L7tZe1LjHqSa2mFqqcY5s8tMZnebzbap2y59sBBC\nCFGFWoS2oJF/I902P5MfaXlp7Di/g7Vn1hITHANA/IWyTQ315pN9n/D0hqe17AaL3YLFbpEsOyGE\nqAISSCgnZ6o7qMUEPx7xMVByIMGZng8w/8B8AFo2chW1y7PYmPCOWtfgVKpnx4PoMH9t+ZONJ1h3\n5ALxCRmlGm9AnL595Rd3qVX5FUO+bvsvp34p1etdyu0r1eJ+/ib/Sxypdh8I9wtncMxgZnaZyd1d\n79aelpsMJka1GEW3Rt34ZXLljK08FEWhe2R3IvwjeLLfk0zvNL3E400GE2F+YVphSeeXGPdgiN1h\n50LOBbp82oWXt74MqEUnJy6ZSIGtgB3nd2jHljRlwl0Dvwbc0/0e/Ewlt+YUQgghqpqv0Zdfb/yV\nWV1naZ0cBkQPIN+WrxUQHtliJOF+4fxzxz8Z+OXAS04RLc7h1MP8c8c/+f7Y9wz8aiBnLp6h54Ke\nzNs3T5veIIQQovJIIKECbut0G6DOL3fe+M5aPatU576+/XXuXnU3g9sHE1k4jSHPYuN8pnpjP6xD\nY93x/VtH8MsjV+NTJFPBXpjZUBKj/58oiusGdt3pdczacA2mkD0YzOmYFB8e7+sqDlgZ8xSdUxAG\nRA+45LE3truRdTetw2wwc3/P+7mvx326/a9e/Sqfjf5M15KxrjEqakqlezDpnd3vMOSbIR7Hnsw8\nyUtbXyIhK4FnrnyG3dN264p+CiGEEHXJnB5zmNBG7cTUv2l/3b77etxHZn4mAOn56aTlla+99uzV\ns3Xro74rfUakEEKIspNAQgXM7DqTOzrfwXWtrtOl7jncbu4tNovWLzncL1x3/qZzmxj09QDevLEb\nAPlWO6H+Zga2aciDw9roMhByC2z4mY08MKyN7jWy8rxPbVhf2JkBwOB7Xrdvzq9zAPCPXojik0yY\nTyQ3tbtJ23/nqjvVsRemBJZVtiWb9Px0ogKjaBnassznX46cGQmHUw/zwuYX2J+8nw/jP9Qdc1XT\nq7TlRUcWERkQyaQ2k2RepxBCiMuG2eiaXnlH5zu0jD8nZ7vGsnIWbr6j8x267cE+wUzrOK1crymE\nEKJ4EkiogBCfEB7q9RB+Jj8CzAHc1eUuAK1VX44lh56f9aTv52rbRH+TP2PjxvLigBd1r/PtybcB\neHTRXjJyLfSMbYCiKPxwb3/emqJ+uKZkq/Pm772mNQtn9tPOzSqmRsKuU24R/cJshAi/CI/jzMEH\niPBtjMlg4t1h7wJwJO0IADcuvZGeC3qSmJ1Yhp8KrD65mqNpR3mo50NlOu9y5gwkTFsxja8Of8WU\nZVOwOdT35aZ2N/G3K/7GKwNfYdG4Rdo5FpvFa2FFIYQQoi5bMGoB9/W4jwd7qnWZ3hz8JhNaqxkL\nzs/GsnAPPtzb/V5t2d/kz8abN/Jon0crOGIhhBBFSSChEmXkq/UKZqycAUBCVoK27/TF02RZsvA3\n+TOm5Rju73E/fkZ1HvvPCd8Cdq0uQoPCYoiNgn21KQ5XtXIFAa5sFcH2J4cBFFts0Wp3ZUUoBvVD\n+cl+T2rb3hn6DgbU6zQJUtsJXtn0SkBtkVRgK+BY+jEAhi8aXuqfwfns8zy5Qb2Os8CgKL7t1E+T\nfuLJfk8ypf0UwvzCaBfejp9v+JnhzYczu/tsr+cIIYQQdVn3yO7c3fVuLVge5hdGn6g+QPkyEpwd\nszqEd8DH6MPvN/3ONTHX8O24bytv0EIIIXQkkFCJbu14KwCJ2Yk8veFpPt73sbZv8bHFZORn0Cqs\nFUaDkZldZ7L5ls34GtX6CP4xHwNqgaFgP1faX6CviY2PD+G56/TtA4N8TRgU2HHS+1xCm92BMfAw\nijELo6K+7sBmAxnfajwNfBswsNlAYkPUSsldGrcAwKAYmNphKn4mP/Zc2OP1dY+mHS2xxeUH8R+4\nxm4OLPa4+sZ9esLYuLE83vdxvhz7JU0LgzjuogKjeGPwG9zc/ubqHKIQQghRY5yZe+UJJCTnqtM5\nZ3VT61SF+YXx7yH/Jqbwe44QQojKJ/1wKlFcaBz/uuZfPLjmQb4/9r1u329nfgOgU0QnbZvRYOSd\noe9w56o7MQUdQzFl4LA2wNesBcy3ywAAFs5JREFUj+80DfPsfOBnNjKqSxNWHTjvsQ8gz5ZHQOw8\nAAouqNkLJsXECwNe0I7pGNGeE5nHdZ0VQnxCyLJk8dff/+rxmg6Hg4lLJhIbHMuyics89j+z8Rm+\nO/qdtm5QJE7l5N566ukrny5VNwshhBCivnB+TpanNpMzkNDQv2GljkkIIUTx5E6vkg2NHcrsbq6U\ndOe8vIOpB1FQaNugre742JBYbVkxqVMb/EylK67XqmEguRabrrijU5bV1YbSodgwKAaPon1zus+h\nfXh7hsS6Ogc4l8/nqAGKES1GEGQO0m07dfGU1/G4BxGEnjPzBErXElMIIYSoT5xTAMtaI6HAVsAz\nG58BIDooutLHJYQQwjsJJFQB94rBfaP6assOHB4tDBsHNKZ3494AKMZsQM02KA1/HxMOB+RZPHsu\nZ1lc0w98G67x2pc5JiSGb8Z9o/vgbR/enls73Kqth/mGaWmGzpoJ4Jl66KwH0TRQTdWPCowq1Z+h\nvnAGY3pG9qzhkQghhBC1j/NhR3JustcHJEVtPLsRq93K8YzjJOcmM7jZYMlIEEKIaiSBhCrgZ/Jj\nVtdZ3NXlLto2aMvjfR8v9lhFUXjqyqfUZS2QULq3xb/wuFyLZ/Q+x1a+PswAkQGR2nKwTzBWR2Eg\nIc0VSJi+Yjo7z+/U1kd+OxKA9699nw03b2Dx+MXlvv7l6IomV3BXl7t465q3anooQgghRK3jbKO9\n5dwWus7vSpdPu5BnzfN67NI/ljLr51kM+XoIpzLVLMl7e9zr9VghhBBVQ2okVJE5PeZoy1M7TGVE\nixGYDWavx0YHRWNSzBj9zgIQn2and4txl7xGgI/69uUUWAkP9NHty7brAwmP9Hqk1GMfED2AdWfW\nMaf7HDaf24zNrgYqjqUfI9AcSLYlm/jkeGasnMGKiSvYlbRLO7d5SPNSX6c+8TH68EDPB2p6GEII\nIUSt1CGiA10bdWX+gfnatoOpBzmadpQB0QN0xYl3JqkPMtLy0/j68NcAxARLYUUhhKhOEkioJiWl\n2/kafWke1IEjOcfxifidN/Z+xY2dh1yy64Gfj5oGmOclIyG3SCDhts63lXqsbRq04ZORnwCw6dwm\nHDiYuWompy+epkvDLtgddrYmbgVg1HejtPP+N+x/pb6GEEIIIYS7W9rfwt4Le7X1v2/6O8fSj9E+\nvD3fjPtG2x5/IV5b3pK4BZBOUUIIUd1kakMt0Sq4M4bCjARA95S/OAGFtRTOZ+brtiddzCMl76y3\nU8rsSNoRADaf20xCVgLRQdF0CO/g9dj+TftXyjWFEEIIUf9cE3MNE9tM1KZHOmszHUo9pB2z9dxW\nDqcd5rE+j3Fn5ztrZJxCCCEkkFBrBJlDURRXcaEDKQc8jsm15rItcZu2HuCrBhKmfrhFd1zfF1eT\nadyJ0VbxokOhPqG69ROZJ7it823c210/F/H94e+jKEqFryeEEEKI+inAHMBzVz1HXFgci8Yt0u1z\nFmBcdXIVAGPjxmp1Ee7pfk/1DlQIIYRMbagtAkz6bg4fxn/IbZ1uw8eo1j5IzE5k+KLhAKyctJLo\noGgiAn09XgfA4HsOAJsxucLjmttnLqPjRlNgK+C+X++jkX8jGvo35C/d/kK/Jv04dfEUscGxdI/s\nXuFrCSGEEEIAtAtvx8abNzJ79Wz2XNjDo789yiO9HyE5N5lWoa0I8wsDYO/0vZd4JSGEEFWhQoEE\nRVFOABcBG2B1OBy9K2NQ9ZGz7RGAv8mfXGsuey/spXeU+iN1FhMCeHnLy/xn6H9oFxWMyaB4tIs0\n+qmtGP2zxpEbtJRWoa3KPa5Q31CuanoVNruNWV1ncUuHW7R93SO7SwBBCCGEEFUi2CeYj0d8TK/P\nerHyxEouWi6yIWEDvRr30o6RbEghhKgZlTG14RqHw9FdgggV0zN8CHZLCAB3dL4DgIz8DG1/Ynai\ntvxbwm/Y7DZ2J+1mzpDWZOVbOXL+orbfN3IFAEmnr2Lx+MV8OurTCo/PaDAyp8ccwv3CK/xaQggh\nhBCl4WP0IdRXnWa5IWED4JrmIIQQouZIjYRaosBqJPvYX+nKc4xrpbZ+zCzIZMWfK/j9zO/kWHO0\nY+0OO+/tfY9pK6aRzXEArn3zN/7761GW7T2HYnIeqxAXFqd9AAshhBBC1DWfjfpMt/7XK/5aQyMR\nQgjhVNEaCQ5glaJWCXzP4XC8X/QARVHuBu4GiI2NreDlLl9qZp5CmwbtCPFRMxMyCzJ5euPTAAyI\nHkDniM7EBMew4sQKVp1Qiw0lF5wA1N7Jr686gsH3HIFx1T9+IYQQQoiq0CK0hW69fXj7mhmIEEII\nTUUzEgY4HI6ewCjgXkVRBhU9wOFwvO9wOHo7HI7ejRo1quDlLl/DOzTmmXEdeWxkewLNgRgUg25q\nw/qE9fgYfRjbaiwAf2T8AcDqC28D9sKj7AQ0fw8A60X5kBVCCCHE5WX5xOU1PQQhhBBUMJDgcDgS\nCv+fBHwP9K2MQdVHBoPC7f1b4u9jxKAYaBrYlD8z/tQdszNpJ9FB0R7nGgPUoILB5wKKMQ+A29s8\nw7ezr6z6gQshhBBCVJOY4JiaHoIQQggqEEhQFCVQUZRg5zJwLbCvsgZW30UHR3M0/ahu2+N9H6d5\nSHNtfUq7KQAENP8IDHk43N7OR0d0pldzKYwohBBCiLpvdrfZvHb1azU9DCGEEIUqkpHQGFivKMoe\nYCuwzOFwrKycYYkIvwhOZp7U1q+IuoKpHaZiMrjKWoyJG6Mt+8d8gqJYAMi/MLT6BiqEEEIIUcXu\n6X4PI1uMrOlhCCGEKFTuQILD4TjucDi6Ff7XyeFwvFiZA6vvWoW10q2n5KVoy9M6TiPUN5Tukd3p\n10SdvmAKOIEpZA8AtlwpaimEEEIIIYQQompI+8daqk1YG916hH+Etvxon0dZP2U9AM9d9ay23bfh\nOnAYeP16yUgQQgghhBBCCFE1Ktr+UVQR91ZHrw16jd5Rvb0e1zSoqW69Z+MeTOjSrSqHJoQQQggh\nhBCiHpOMhFoqMiBSWx7ZciQN/RsWe+zi8Yu15cNph6p0XEIIIYQQQggh6jcJJNRSgeZAFoxawKab\nN13y2LiwOBaMWgBAl4ZdqnpoQgghhBBCCCHqMZnaUIt1j+xepmPnj5pP67DWVTgiIYQQQgghhBD1\nnQQSLiM9InvU9BCEEEIIIYQQQlzmZGqDEEIIIYQQQgghSk0CCUIIIYQQQgghhCg1CSQIIYQQQggh\nhBCi1CSQIIQQQgghhBBCiFKTQIIQQgghhBBCCCFKTQIJQgghhBBCCCGEKDUJJAghhBBCCCGEEKLU\nJJAghBBCCCGEEEKIUpNAghBCCCGEEEIIIUpNAglCCCGEEEIIIYQoNQkkCCGEEEIIIYQQotQkkCCE\nEEIIIYQQQohSk0CCEEIIIYQQQgghSk0CCUIIIYQQQgghhCg1CSQIIYQQQgghhBCi1BSHw1F9F1OU\nC8DJarugKK2GQHJND0KUm7x/dZ+8h3WbvH91n7yHdZu8f3WfvId1m7x/dZ/zPWzucDgaleaEag0k\niNpJUZTtDoejd02PQ5SPvH91n7yHdZu8f3WfvId1m7x/dZ+8h3WbvH91X3neQ5naIIQQQgghhBBC\niFKTQIIQQgghhBBCCCFKTQIJAuD9mh6AqBB5/+o+eQ/rNnn/6j55D+s2ef/qPnkP6zZ5/+q+Mr+H\nUiNBCCGEEEIIIYQQpSYZCUIIIYQQQgghhCg1CSQIIYQQQgghhBCi1CSQIIQQQgghhBBCiFKTQEI9\noyiKUtNjEGWnKErDwv/L+1dHKYrSU1GUiJoeh6gY+TdYtymKIt976ihFUYw1PQZRMYqiRBX+X36P\n1kGKovRXFKVVTY9DlJ/z92hl/RuUD9TLnKIofRRFeV9RlAcURQlySHXNOkVRlB6KoiwHHgKQ96/u\nKXwP/7+9e4+1q6zTOP59oFCFcouC1uAlwagoOmINFwOWsYNovFBEECVaHeNkLqCjiEYFrIHoZAzO\nWLlakQIGBBEvKaIIOCVW6XAbxmAcQG2Cojhyh1rQ9vGP991wpnNO3af7sNd62+eTNO3Za63d385z\n1t5r/9a73nUVsAqY1XU9MT2S9pe0RNK7IftgiyTtI+n9ALbXd11PTI+kV0q6ADgpX2LaVD8HrwZO\nhryPtqaeCLkSuAbYqet6YvrqscxS4IOSdpipfTCNhM2UpFmSzgTOpHyBOQT4926rimFJ2krSecC5\nwIW2P9F1TTE9kmZLOgtYCpwBXAu8oS7L2ZgGSHorcBpwPbBA0imS9uq4rJgGSf8MfAM4QdLr62M5\ns92A+jl4GnA2cDUwF1gsabtuK4thqfg34HzgPNvv67qmGJ6kbSSdTbkt4BLge8BBdVm+QzZC0nzK\nscw1wLOAj0s6ZCaeO78Emy8DPwYOsn0OcAKwPgdQbahnzXYBfmr7KwCSds0X0KbMBW4EDrB9GXAl\n8DRJytmYZrwEuMz2BcDxwL7AEZJ27rasmIY7gDcC/wB8DMD2uryX9l/9HLwGWGB7GfCvlGObP3VZ\nVwyvftbNAW62fT6ApD3yJbQZs4EVwIG2lwNfB/aUNCuju5ryCmCl7Ysoo4KeARw1uNRoFNmRNyOS\njpR0nKT9bK+zfb7th2vXaQWwK/ApSRmW1EM1vw9JOqA+tAh4raTjJf2A0g3+oqRdu6syNqZm+GFJ\n+9hebXup7bV18Rzg2badhl4/TdgH968P3Qs8RdJOtn8L3A08F9h/yieJTknaT9ILJjx0OfDf9e+H\nB5c4ANkHe2jD/GxfZvt+SQcDN1AatJ+WtGdnRcZGTbIPHgfsK+lESSuBzwLLJM3rpsLYmA3ye8T2\nhbb/UH+eBayz/ac0g/prkn3wNmBnSXNt3wc8DGwLLBz1/8ovwWZA0taSTgI+SunWL5V02IRVtgKO\nqn92B94radvxVxqT2SA/gDMlHVl39s9T5kdYDBwD7AAcLSnX2vfIBhmuB86R9Ja6bPA++03gzZK2\ns72uo1JjEpPsg0trA/Y/gd2AL0m6hPLl8yFKNz+XqPSIpJ0lXQ58HzhS0vaDRbWxvhY4lfL593Tb\nOavdI1PlN2Efuw94h+2DgUeARZKe0U21MZmpMrT9IHA68FbKqKC3A78BDs+Jkf6YLL964kMTjmNW\nAIdJ2iUjEvpnkgzn1EW3AQ8C50n6OvBs4GbKCa6RjmXSSNgM1C8lLwSOs/054JPAsYOOve0rbF9u\n+1HKtaKHAn/srOD4P6bI758kvcD2ycCLba+wfQ9wEbAwB8H9MkWGx0jac8KH7f9Shum+qKMyYwqT\n5LeYchbtIcqB76XAd22/nTLnzOvrdrlEpT+2p1y/e2z996vh/02u+B/AdXUdJO0z3hJjI6bKz/Xv\nG2x/p657BbA3sKaDOmNqk2YIYHsJ5VLba+ux6DeBV5IM+2TKfdD2+tpMWF3Xmd9VkbFRU2V4O/Ah\n4DPA12wfBtxKne9ilGOZNBIaJeldkuZPuFb3bmCXet3SZcBPgbdN0mV6HuUsW4Z1dmiI/H4CvEPS\nVrbvn7DpHsCqDI3v3jT2wUFWDwPPp4waytnsjv2F/C4FbgeOsn2v7Yttf7mu90LKQXB0bEKGO9r+\nNWVCsEuAtZSh1M+q6wkebxidAnxU0gPAK7IfdmfY/CYxj3JGOw31jk0nwzrKcmAe8Csgo/M6NJ33\n0NqUnV03XTt4vIu64wl/IcN9Bhnafsz2D2x/tW46D/juqP9/GgkNqcOL5qpcL78IOBo4vQ5d+T3w\nUuowFeALwGHAM1Vmj3+dpOuAvwHOzhnt8dvE/AZDqBdIWgW8BliaofHd2MQMdwOwfS9wDyXDnM3u\nwDTzWwIcKmlu3XaBpFspZ0J/OP7qA6bM8Mx6ucJa22uAqyiT1T6+r6ncAeD5wIXASsokqGdlPxyv\nTcmvbrejpIMlXQ+8Dvj0hOu2Y4xGyHC2pIMk3UC5k9i/TJhDKMZkhPfQrW0/QvnuuN/g8W5exZZt\nU/fBuu0Bkm4EDgSWj1pLGgmNqDuwKdfI/9r2Asos1A9SDnjPAF4FvEzlGuz/AX4GvKUOI9uJ8qb9\nJtt3dPMqtlwj5Hd4fYrtKfm9Mfl1Y4QMj5jwNItsnzrm0oOR8juyPsVq4IS6D9459hcQG8vwXspZ\nGABsr6Tk9SJJO9U811OyPsn2Ats/Gf8r2LKNkN9T6nX2Bk6pxzG3jf8VxAgZPrUeiz5GMuzMiO+h\ngxNYf2t78Xgrj4ERMhzMG/QL4ETbh9hePWo9mbCt51SGRZ8MbC3pO8CO1KFgLrewOoYyxO9UypmW\noyizGl9MGfZ3Q1334vFXHzOQ3/V13W+Pv/qAGclw1eC56sFwjNEM5HddXffnwM/H/gJimAw/ANwl\nab7tFXWzpZTLGL4PPFfSPNu/An43/lewZRsxv6uA50ja2/ZVHZQfzGiGP+qg/C3eDL2H7m37LtuP\ndfAStngz/Dl410zVlREJPSZpPuU+9LtQ7oV9MmWSxL9WnSSqdgg/BXzW5R69VwLvknQzpVGUsy4d\nSX7tS4ZtS37tGzLD9ZQJMhdP2PQNwD8CtwAvrQdPMWYzkN9/UfKbsQPfmJ5k2LYZfA9Nfh3p8+eg\ncnlLf0k6EHie7Qvqz2dQDmr/ABxre57KLKq7AacBH7R9p6RnAtvZ/kVXtUfy2xwkw7Ylv/ZNM8Ml\nwEdsr5Z0KHCf7Wu7qj2S3+YgGbYt+bWvzxlmREK/3QhcoidmfV8JPMf2MsrQlmNrB2p34I+D63Zt\n/zYHwL2Q/NqXDNuW/No3nQzXDa75tP2tHAD3QvJrXzJsW/JrX28zTCOhx2yvsf2on5jg5GDKvegB\n3gPsKWk5cBFwUxc1xtSSX/uSYduSX/s2JUMptyTri+TXvmTYtuTXvj5nmMkWG1A7UKbcCnAw6d5D\nwMeBvYBfutw7NHoo+bUvGbYt+bVvOhk612z2TvJrXzJsW/JrXx8zzIiENqwHtqHc5/xltet0IrDe\n9g9zANx7ya99ybBtya99ybBtya99ybBtya99vcswky02QtJ+wI/qn3Ntn9NxSTENya99ybBtya99\nybBtya99ybBtya99fcswjYRGSNodeCfwOduPdl1PTE/ya18ybFvya18ybFvya18ybFvya1/fMkwj\nISIiIiIiIiKGljkSIiIiIiIiImJoaSRERERERERExNDSSIiIiIiIiIiIoaWREBERERERERFDSyMh\nIiIiIiIiIoaWRkJERERMSdJiSR/eyPKFkl48zpoiIiKiW2kkRERExCgWAmkkREREbEFku+saIiIi\nokckfQJYBPwOuBO4EXgA+DtgW+AO4J3Ay4HlddkDwOH1KU4HdgXWAO+z/bNx1h8RERFPrjQSIiIi\n4nGS5gHLgH2BWcBNwFnAubbvqeucAtxt+wuSlgHLbV9al10N/L3t2yXtC3zG9mvG/0oiIiLiyTKr\n6wIiIiKiVw4EvmF7DYCkb9fH96oNhJ2BOcD3NtxQ0hzgVcDXJA0env2kVxwRERFjlUZCREREDGMZ\nsND2LZLeDRw0yTpbAffbfvkY64qIiIgxy2SLERERMdG1wEJJT5W0A/Cm+vgOwG8kbQMcPWH9h+oy\nbD8I/FLSEQAq/mp8pUdERMQ4pJEQERERj7N9E3AxcAtwBXB9XXQisApYCUycPPGrwPGSbpa0B6XJ\n8F5JtwC3AoeOq/aIiIgYj0y2GBERERERERFDy4iEiIiIiIiIiBhaGgkRERERERERMbQ0EiIiIiIi\nIiJiaGkkRERERERERMTQ0kiIiIiIiIiIiKGlkRARERERERERQ0sjISIiIiIiIiKG9mfaHW1j0wrB\nzQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f97efefe7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "data.plot(figsize=(18,8))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>JNPR_p</th>\n",
       "      <th>JNPR_v</th>\n",
       "      <th>HPQ_p</th>\n",
       "      <th>HPQ_v</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2002-01-02</th>\n",
       "      <td>19.762895</td>\n",
       "      <td>16.467801</td>\n",
       "      <td>7.517142</td>\n",
       "      <td>15.635064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-03</th>\n",
       "      <td>20.903610</td>\n",
       "      <td>16.721778</td>\n",
       "      <td>7.971990</td>\n",
       "      <td>16.179228</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-04</th>\n",
       "      <td>20.466336</td>\n",
       "      <td>16.686654</td>\n",
       "      <td>8.041432</td>\n",
       "      <td>15.750100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-07</th>\n",
       "      <td>20.570902</td>\n",
       "      <td>16.666379</td>\n",
       "      <td>7.992822</td>\n",
       "      <td>15.777702</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-01-08</th>\n",
       "      <td>20.342759</td>\n",
       "      <td>16.617694</td>\n",
       "      <td>7.909491</td>\n",
       "      <td>15.321209</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               JNPR_p     JNPR_v     HPQ_p      HPQ_v\n",
       "date                                                 \n",
       "2002-01-02  19.762895  16.467801  7.517142  15.635064\n",
       "2002-01-03  20.903610  16.721778  7.971990  16.179228\n",
       "2002-01-04  20.466336  16.686654  8.041432  15.750100\n",
       "2002-01-07  20.570902  16.666379  7.992822  15.777702\n",
       "2002-01-08  20.342759  16.617694  7.909491  15.321209"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data=data.dropna(axis=1)\n",
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Use SP500 continous future contract as baseline\n",
    "sp500_baseline=quandl.get(\"CHRIS/CME_SP1\")['Last'].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_tech_data(pair):\n",
    "    p1_c,v1_c,p2_c,v2_c=tuple(pair.columns)\n",
    "    s1_name,s2_name=p1_c.split('_')[0],p2_c.split('_')[0]\n",
    "    p1=pair[p1_c].values\n",
    "    p2=pair[p2_c].values\n",
    "    spread=p1-p2\n",
    "    v1=pair[v1_c].values\n",
    "    v2=pair[v2_c].values\n",
    "    sample = pair.copy()\n",
    "    sample[s1_name + '_mom'] = talib.MOM(p1)\n",
    "    sample[s1_name + '_macd'], sample[s1_name + '_macd_sig'], sample[s1_name + '_macd_hist'] = talib.MACD(p1)\n",
    "    sample[s1_name + '_rsi'] = talib.RSI(p1, timeperiod=10)\n",
    "    sample[s1_name + '_cmo'] = talib.CMO(p1)\n",
    "    sample[s2_name + '_mom'] = talib.MOM(p2)\n",
    "    sample[s2_name + '_macd'], sample[s2_name + '_macd_sig'], sample[s2_name + '_macd_hist'] = talib.MACD(p2)\n",
    "    sample[s2_name + '_rsi'] = talib.RSI(p2, timeperiod=10)\n",
    "    sample[s2_name + '_cmo'] = talib.CMO(p2)\n",
    "    sample['spread'] = spread\n",
    "    sample['diff'] = sample['spread'] / sample['spread'].shift(1)\n",
    "#     spread=p1-p2\n",
    "#     data['spread'+'_mom'] = talib.MOM(spread)\n",
    "#     data['spread'+'_macd'], data['spread'+'_macd_sig'], data['spread'+'_macd_hist'] = talib.MACD(spread)\n",
    "#     data['spread'+'_rsi'] = talib.RSI(spread,timeperiod=10)\n",
    "#     data['spread'+'_cmo'] = talib.CMO(spread)\n",
    "    sample=sample.dropna()\n",
    "    return sample\n",
    "z_score= lambda x:(x-x.mean(axis=0))/x.std(axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "full_features=generate_tech_data(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>JNPR_p</th>\n",
       "      <th>JNPR_v</th>\n",
       "      <th>HPQ_p</th>\n",
       "      <th>HPQ_v</th>\n",
       "      <th>JNPR_mom</th>\n",
       "      <th>JNPR_macd</th>\n",
       "      <th>JNPR_macd_sig</th>\n",
       "      <th>JNPR_macd_hist</th>\n",
       "      <th>JNPR_rsi</th>\n",
       "      <th>JNPR_cmo</th>\n",
       "      <th>HPQ_mom</th>\n",
       "      <th>HPQ_macd</th>\n",
       "      <th>HPQ_macd_sig</th>\n",
       "      <th>HPQ_macd_hist</th>\n",
       "      <th>HPQ_rsi</th>\n",
       "      <th>HPQ_cmo</th>\n",
       "      <th>spread</th>\n",
       "      <th>diff</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2002-02-20</th>\n",
       "      <td>9.610528</td>\n",
       "      <td>17.114199</td>\n",
       "      <td>6.881744</td>\n",
       "      <td>15.490792</td>\n",
       "      <td>-3.232027</td>\n",
       "      <td>-2.282527</td>\n",
       "      <td>-2.020381</td>\n",
       "      <td>-0.262146</td>\n",
       "      <td>18.663303</td>\n",
       "      <td>-59.516840</td>\n",
       "      <td>-0.545123</td>\n",
       "      <td>-0.252159</td>\n",
       "      <td>-0.220186</td>\n",
       "      <td>-0.031973</td>\n",
       "      <td>32.565208</td>\n",
       "      <td>-24.894429</td>\n",
       "      <td>2.728784</td>\n",
       "      <td>-0.058857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-02-21</th>\n",
       "      <td>9.163747</td>\n",
       "      <td>16.891675</td>\n",
       "      <td>6.756747</td>\n",
       "      <td>15.567715</td>\n",
       "      <td>-3.973492</td>\n",
       "      <td>-2.333322</td>\n",
       "      <td>-2.082970</td>\n",
       "      <td>-0.250353</td>\n",
       "      <td>17.235192</td>\n",
       "      <td>-61.732422</td>\n",
       "      <td>-0.482625</td>\n",
       "      <td>-0.268590</td>\n",
       "      <td>-0.229867</td>\n",
       "      <td>-0.038723</td>\n",
       "      <td>29.356646</td>\n",
       "      <td>-29.775461</td>\n",
       "      <td>2.407000</td>\n",
       "      <td>-0.321784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-02-22</th>\n",
       "      <td>8.992640</td>\n",
       "      <td>16.963174</td>\n",
       "      <td>6.697721</td>\n",
       "      <td>15.601654</td>\n",
       "      <td>-3.754855</td>\n",
       "      <td>-2.360178</td>\n",
       "      <td>-2.138411</td>\n",
       "      <td>-0.221767</td>\n",
       "      <td>16.691685</td>\n",
       "      <td>-62.577136</td>\n",
       "      <td>-0.524290</td>\n",
       "      <td>-0.283111</td>\n",
       "      <td>-0.240516</td>\n",
       "      <td>-0.042595</td>\n",
       "      <td>27.913612</td>\n",
       "      <td>-32.022125</td>\n",
       "      <td>2.294919</td>\n",
       "      <td>-0.112081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-02-25</th>\n",
       "      <td>9.410902</td>\n",
       "      <td>16.579613</td>\n",
       "      <td>6.937297</td>\n",
       "      <td>15.841222</td>\n",
       "      <td>-3.792879</td>\n",
       "      <td>-2.320956</td>\n",
       "      <td>-2.174920</td>\n",
       "      <td>-0.146036</td>\n",
       "      <td>23.264109</td>\n",
       "      <td>-53.648756</td>\n",
       "      <td>-0.145829</td>\n",
       "      <td>-0.272150</td>\n",
       "      <td>-0.246843</td>\n",
       "      <td>-0.025307</td>\n",
       "      <td>40.994081</td>\n",
       "      <td>-15.825049</td>\n",
       "      <td>2.473605</td>\n",
       "      <td>0.178686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2002-02-26</th>\n",
       "      <td>9.686575</td>\n",
       "      <td>16.669812</td>\n",
       "      <td>6.947714</td>\n",
       "      <td>16.100400</td>\n",
       "      <td>-4.458296</td>\n",
       "      <td>-2.241786</td>\n",
       "      <td>-2.188293</td>\n",
       "      <td>-0.053493</td>\n",
       "      <td>27.455376</td>\n",
       "      <td>-47.884210</td>\n",
       "      <td>-0.291658</td>\n",
       "      <td>-0.259630</td>\n",
       "      <td>-0.249400</td>\n",
       "      <td>-0.010230</td>\n",
       "      <td>41.506831</td>\n",
       "      <td>-15.163501</td>\n",
       "      <td>2.738861</td>\n",
       "      <td>0.265257</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              JNPR_p     JNPR_v     HPQ_p      HPQ_v  JNPR_mom  JNPR_macd  \\\n",
       "date                                                                        \n",
       "2002-02-20  9.610528  17.114199  6.881744  15.490792 -3.232027  -2.282527   \n",
       "2002-02-21  9.163747  16.891675  6.756747  15.567715 -3.973492  -2.333322   \n",
       "2002-02-22  8.992640  16.963174  6.697721  15.601654 -3.754855  -2.360178   \n",
       "2002-02-25  9.410902  16.579613  6.937297  15.841222 -3.792879  -2.320956   \n",
       "2002-02-26  9.686575  16.669812  6.947714  16.100400 -4.458296  -2.241786   \n",
       "\n",
       "            JNPR_macd_sig  JNPR_macd_hist   JNPR_rsi   JNPR_cmo   HPQ_mom  \\\n",
       "date                                                                        \n",
       "2002-02-20      -2.020381       -0.262146  18.663303 -59.516840 -0.545123   \n",
       "2002-02-21      -2.082970       -0.250353  17.235192 -61.732422 -0.482625   \n",
       "2002-02-22      -2.138411       -0.221767  16.691685 -62.577136 -0.524290   \n",
       "2002-02-25      -2.174920       -0.146036  23.264109 -53.648756 -0.145829   \n",
       "2002-02-26      -2.188293       -0.053493  27.455376 -47.884210 -0.291658   \n",
       "\n",
       "            HPQ_macd  HPQ_macd_sig  HPQ_macd_hist    HPQ_rsi    HPQ_cmo  \\\n",
       "date                                                                      \n",
       "2002-02-20 -0.252159     -0.220186      -0.031973  32.565208 -24.894429   \n",
       "2002-02-21 -0.268590     -0.229867      -0.038723  29.356646 -29.775461   \n",
       "2002-02-22 -0.283111     -0.240516      -0.042595  27.913612 -32.022125   \n",
       "2002-02-25 -0.272150     -0.246843      -0.025307  40.994081 -15.825049   \n",
       "2002-02-26 -0.259630     -0.249400      -0.010230  41.506831 -15.163501   \n",
       "\n",
       "              spread      diff  \n",
       "date                            \n",
       "2002-02-20  2.728784 -0.058857  \n",
       "2002-02-21  2.407000 -0.321784  \n",
       "2002-02-22  2.294919 -0.112081  \n",
       "2002-02-25  2.473605  0.178686  \n",
       "2002-02-26  2.738861  0.265257  "
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "full_features.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Prepare data\n",
    "baseline_diff=(sp500_baseline/sp500_baseline.shift(1))[full_features.index[0]:]\n",
    "price=data[full_features.index[0]:]\n",
    "f_data=full_features\n",
    "z_data=full_features['diff']\n",
    "feature_number=f_data.shape[1]\n",
    "# tao=0.8\n",
    "target_profit=2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [],
   "source": [
    "class DRL_PairsTrading(object):\n",
    "    def __init__(self, feature_number, dense_units_list=[1024, 768, 512, 256], rnn_hidden_layer_number=4, rnn_hidden_units_number=128, learning_rate=0.001):\n",
    "        tf.reset_default_graph()\n",
    "        self.f = tf.placeholder(dtype=tf.float32, shape=[None, feature_number], name='environment_features')\n",
    "        self.z = tf.placeholder(dtype=tf.float32, shape=[None, 1], name='environment_return')\n",
    "        self.c = tf.placeholder(dtype=tf.float32, shape=[], name='environment_fee')\n",
    "        self.dropout_keep_prob = tf.placeholder(dtype=tf.float32, shape=[], name='dropout_keep_prob')\n",
    "        self.hidden_rnn_init_state = tf.placeholder(tf.float32, [rnn_hidden_layer_number, 1, rnn_hidden_units_number], name='hidden_rnn_initial_state')\n",
    "        self._state_per_layer_list = tf.unstack(self.hidden_rnn_init_state, axis=0)\n",
    "        self.rnn_tuple_state = tuple(self._state_per_layer_list)\n",
    "        self.previous_rnn_output = tf.placeholder(dtype=tf.float32, shape=[1, rnn_hidden_units_number], name='previous_rnn_output')\n",
    "        \n",
    "        with tf.variable_scope('feed_forward', initializer=tf.contrib.layers.xavier_initializer(uniform=False), regularizer=tf.contrib.layers.l2_regularizer(0.01)):\n",
    "            self.dense_output = self.f\n",
    "            for u_number in dense_units_list:\n",
    "                self.dense_output = self._add_dense_layer(self.dense_output, output_shape=u_number, drop_keep_prob=self.dropout_keep_prob)\n",
    "            self.dense_output = self._add_dense_layer(self.dense_output, output_shape=rnn_hidden_units_number, drop_keep_prob=self.dropout_keep_prob)\n",
    "        \n",
    "        with tf.variable_scope('rnn', initializer=tf.contrib.layers.xavier_initializer(uniform=False), regularizer=tf.contrib.layers.l2_regularizer(0.01)):\n",
    "            rnn_hidden_cells = [self._add_gru_cell(rnn_hidden_units_number)] * rnn_hidden_layer_number\n",
    "            layered_cell = tf.contrib.rnn.MultiRNNCell(rnn_hidden_cells)\n",
    "            self.zero_state = layered_cell.zero_state(1, dtype=tf.float32)\n",
    "            rnn_input = tf.expand_dims(self.dense_output, axis=0)\n",
    "            self.rnn_outputs, self.current_state = tf.nn.dynamic_rnn(layered_cell, initial_state=self.rnn_tuple_state, inputs=rnn_input)\n",
    "            self.current_output = tf.reshape(self.rnn_outputs[0][-1], [1, rnn_hidden_units_number])\n",
    "            self.rnn_outputs = tf.concat((self.previous_rnn_output, tf.unstack(self.rnn_outputs, axis=0)[0]), axis=0)\n",
    "        with tf.variable_scope('action', initializer=tf.contrib.layers.xavier_initializer(uniform=False), regularizer=tf.contrib.layers.l2_regularizer(0.01)):\n",
    "            self.action = tf.contrib.layers.fully_connected(num_outputs=1, inputs=self.rnn_outputs, activation_fn=tf.tanh)\n",
    "        with tf.variable_scope('reward'):\n",
    "            self.log_reward_t = tf.log(self.z) * self.action[:-1] - self.c * tf.abs(self.action[1:] - self.action[:-1])\n",
    "            self.cum_log_reward = tf.reduce_sum(self.log_reward_t)\n",
    "            self.reward_t = tf.exp(self.log_reward_t)\n",
    "            self.cum_reward = tf.reduce_prod(self.reward_t)\n",
    "        with tf.variable_scope('train'):\n",
    "            optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)\n",
    "            self.train_op = optimizer.minimize(-self.cum_reward)\n",
    "        self.init_op = tf.global_variables_initializer()\n",
    "        self.saver = tf.train.Saver()\n",
    "        self.session = tf.Session()\n",
    "    \n",
    "    def init_model(self):\n",
    "        self.session.run(self.init_op)\n",
    "    \n",
    "    def get_rnn_zero_state(self):\n",
    "        zero_states = self.session.run([self.zero_state])[0]\n",
    "        return zero_states\n",
    "    \n",
    "    def _add_dense_layer(self, inputs, output_shape, drop_keep_prob, act=tf.nn.tanh):\n",
    "        output = tf.contrib.layers.fully_connected(activation_fn=act, num_outputs=output_shape, inputs=inputs)\n",
    "        output = tf.nn.dropout(output, drop_keep_prob)\n",
    "        return output\n",
    "    \n",
    "    def _add_gru_cell(self, units_number):\n",
    "        return tf.contrib.rnn.GRUCell(num_units=units_number)\n",
    "    \n",
    "    def build_feed_dict(self, batch_F, batch_Z, keep_prob, fee, rnn_hidden_init_state, previous_output):\n",
    "        return {\n",
    "            self.f: batch_F,\n",
    "            self.z: batch_Z,\n",
    "            self.dropout_keep_prob: keep_prob,\n",
    "            self.hidden_rnn_init_state: rnn_hidden_init_state,\n",
    "            self.previous_rnn_output: previous_output,\n",
    "            self.c: fee\n",
    "        }\n",
    "    \n",
    "    def train(self, feed):\n",
    "        self.session.run([self.train_op], feed_dict=feed)\n",
    "    \n",
    "    def load_model(self, model_file='./trade_model_checkpoint/trade_model'):\n",
    "        self.saver.restore(self.session, model_file)\n",
    "    \n",
    "    def save_model(self, model_path='./trade_model_checkpoint'):\n",
    "        if not os.path.exists(model_path):\n",
    "            os.mkdir(model_path)\n",
    "        model_file = model_path + '/trade_model'\n",
    "        self.saver.save(self.session, model_file)\n",
    "    \n",
    "    def trade(self, feed):\n",
    "        rewards, cum_reward, actions, current_state, current_rnn_output = self.session.run([self.log_reward_t, self.cum_log_reward, self.action, self.current_state, self.current_output], feed_dict=feed)\n",
    "        return rewards, cum_reward, actions, current_state, current_rnn_output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "metadata": {},
   "outputs": [],
   "source": [
    "model= DRL_PairsTrading(feature_number=feature_number)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [],
   "source": [
    "def batch_nomorlize(sample):\n",
    "    return z_score(sample)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "train_reward: 14.65358\n"
     ]
    }
   ],
   "source": [
    "model.init_model()\n",
    "train_period=9\n",
    "sequence_length=400\n",
    "max_epoch=200\n",
    "fee=1e-1\n",
    "hidden_initial_state=model.get_rnn_zero_state()\n",
    "current_rnn_output=hidden_initial_state[-1]\n",
    "for e in range(max_epoch):\n",
    "    train_actions=np.zeros(train_period*sequence_length)\n",
    "    train_reward=np.zeros(train_period*sequence_length)\n",
    "    baseline=baseline_diff[:(train_period*sequence_length)]\n",
    "    mean_cum_reward=[]\n",
    "    for batch in range(train_period):\n",
    "        batch_f=batch_nomorlize(f_data[(batch*sequence_length):(batch+1)*sequence_length])\n",
    "        batch_z=np.expand_dims(z_data[(batch*sequence_length):(batch+1)*sequence_length],axis=1)\n",
    "        feed=model.build_feed_dict(batch_F=batch_f,\n",
    "                                   batch_Z=batch_z,\n",
    "                                   keep_prob=0.8,\n",
    "                                   fee=fee,\n",
    "                                   rnn_hidden_init_state=hidden_initial_state,\n",
    "                                   previous_output=current_rnn_output)\n",
    "        model.train(feed)\n",
    "        rewards, cum_reward, actions, hidden_initial_state, current_rnn_output=model.trade(feed)\n",
    "        train_reward[(batch*sequence_length):(batch+1)*sequence_length]=rewards.flatten()\n",
    "        train_actions[(batch*sequence_length):(batch+1)*sequence_length]=actions[:-1].flatten()\n",
    "        mean_cum_reward.append(cum_reward.ravel())\n",
    "    print(\"train_reward:\", np.mean(mean_cum_reward))\n",
    "    if np.mean(mean_cum_reward)>10: break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 251,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f97b4dbd208>]"
      ]
     },
     "execution_count": 251,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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eiEQvJfoocMHfAueH+Un/zqzJPsAXa3b5y8wgv7CYgQ8dueL/Qe925YYzVqa4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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f97b4c67128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(np.cumsum(train_reward))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 252,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "18.867058\n"
     ]
    }
   ],
   "source": [
    "# model.init_model()\n",
    "test_f=batch_nomorlize(f_data[sequence_length*train_period:])\n",
    "test_z=np.expand_dims(z_data[sequence_length*train_period:],axis=1)\n",
    "# hidden_initial_state=model.get_rnn_zero_state()\n",
    "# current_rnn_output=hidden_initial_state[-1]\n",
    "feed=model.build_feed_dict(batch_F=test_f,\n",
    "                                   batch_Z=test_z,\n",
    "                                   keep_prob=1.0,\n",
    "                                   fee=fee,\n",
    "                                   rnn_hidden_init_state=hidden_initial_state,\n",
    "                                   previous_output=current_rnn_output)\n",
    "rewards, cum_reward, actions, hidden_initial_state, current_rnn_output=model.trade(feed)\n",
    "print(cum_reward)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 253,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.lines.Line2D at 0x7f97b45c8048>"
      ]
     },
     "execution_count": 253,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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VQ/3M10s6KhWnv/41lLfemtw4VOE450mSJEkqj+Z9A/+9I3ffifcn6tnJBZU/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\nYJAkSZIkSa39CwQXt2IkyMTqAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f97b46072b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "total_rewards=np.cumsum(np.concatenate((train_reward,rewards.flatten())))\n",
    "total_actions=np.concatenate((train_actions,actions[:-1].flatten()))\n",
    "total_spread=full_features['spread']\n",
    "pd.DataFrame({'reward':total_rewards,'action':total_actions,'spread':total_spread},index=f_data.index).plot(figsize=(18,8))\n",
    "plt.axvline(z_data[:train_period*sequence_length].index[-1],color='red',linestyle='--')\n",
    "# The test result of 300 days seems OK,keeps the uptrend\n",
    "# The output actions can be used in back testing"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3.0
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 0
}